Data Career Transformations
Data Career Transformations is the show where we watch Analytics Engineers. Data Engineers, Data Analysts & Data scientists TRANSFORM their careers. Hosted by Bolaji Oyejide, dbt Community Manager. About the dbt Community: We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. dbt Community - for and by data pros. * Build reliable transformation pipelines. * Test & deploy models. * Optimize queries. * Structure data for self-serve analysis. Come hang out and transform with 70,000 of the brightest Analytics Engineers, Data Engineers, Data Analysts, and Data Scientists in the world. Join the dbt Community getdbt.com/community The podcast is sponsored by dbt Labs, makers of the data transformation framework dbt. To reach our team, drop a note to [email protected]
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25: From COBOL Developer to Insurance Data Engineer: Brad Cronkrite
09/02/2025
25: From COBOL Developer to Insurance Data Engineer: Brad Cronkrite
Description: In this conversation, Brad Cronkrite shares his journey from a developer to a lead data analytics engineer at Mercury Insurance. He discusses the critical role of data in the insurance industry, the challenges and opportunities presented by AI, and the importance of mentorship and self-awareness in career growth. Brad also emphasizes the significance of maintaining a work-life balance and understanding the dynamics of introversion in the workplace. He shares insights on empowering analytics teams through dbt mesh and reflects on past data disasters that shaped his approach to data engineering. Takeaways: Brad's journey in data began as a developer on a mainframe. Data is foundational in the insurance industry, influencing pricing and risk assessment. Empowering analytics teams with dbt mesh allows for greater flexibility and ownership. Finding your niche in data can lead to greater job satisfaction. Day-to-day work in data engineering involves project management and troubleshooting. AI can enhance workflows but must be used responsibly in decision-making. Data disasters can lead to valuable learning experiences and improved processes. Interviewing for data roles often reveals knowledge gaps that need addressing. Understanding introversion can improve team dynamics and productivity. Measuring success in data work involves visibility and trust from leadership. Chapters: 00:00 Brad's Journey into Data 02:44 Navigating Imposter Syndrome 05:38 Data's Role in the Insurance Industry 08:22 Empowering Analytics Teams with dbt Mesh 10:58 Finding Your Niche in Data Engineering 13:27 The Structure of Brad's Data Team 16:10 Building a Robust CI/CD Pipeline 19:07 The Role of AI in Data Engineering 21:44 Navigating Data Disasters 24:15 Interview Insights and Challenges 26:53 Understanding Introversion in the Workplace 32:22 Proud Projects and Their Impact 36:03 Mentorship and Career Growth 37:14 Advice for Aspiring Data Professionals Speakers: Guest: Brad Cronkrite, Lead Data Analytics Engineer, Mercury Insurance Host: , Community Manager at dbt Labs We’re Building the Future of Data. Together. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi—
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23: From Nonprofit & Education, to Senior BI Analyst @ JustWorks: Millie Symns
08/31/2025
23: From Nonprofit & Education, to Senior BI Analyst @ JustWorks: Millie Symns
In this episode of Data Career Transformations, Bolaji interviews Millie Symns, a senior Business Intelligence analyst at JustWorks. Millie shares her journey into the data field, emphasizing the importance of mission-driven work and the intersection of data and education. She discusses her current role, the challenges of communicating data insights to non-technical stakeholders, and the significance of mentorship in the data community. Millie's insights on data literacy, measuring business impact, and the value of collaboration highlight the evolving landscape of data careers. Chapters: 02:48 Millie's Journey into Data 05:36 The Intersection of Data and Mission-Driven Work 08:19 Millie's Data Origin Story 11:06 Current Role at JustWorks 13:47 Career Path and Previous Roles 16:32 Stakeholder Communication Challenges 19:09 Data Literacy and Its Impact 24:29 Understanding Data Through Personal Experience 28:18 The Pressure of Quick Answers in Data 29:10 Navigating Business Context as a Data Analyst 32:29 Celebrating Small Wins in Data Projects 35:51 Measuring Business Impact of Data Work 39:45 The Importance of Mentorship in Data Careers Takeaways: Millie's journey into data began with a passion for education and access to resources. She emphasizes the importance of mission-driven work in the data field. Millie's first job involved education evaluation, which shaped her data career. She transitioned from nonprofit to corporate, bringing her mission focus with her. Millie values the role of data in solving collective issues rather than individual problems. Her current role at JustWorks involves helping stakeholders make data-driven decisions. Millie highlights the challenges of communicating data insights to non-technical stakeholders. Data literacy varies across industries and impacts the quality of stakeholder requests. Measuring the impact of data work is challenging but essential for data professionals. Mentorship is crucial for growth in the data field, both as a mentor and mentee. Speakers: Guest: , Senior BI Analyst at JustWorks Host: , Community Manager at dbt Labs We’re Building the Future of Data. Together. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi—
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22: From Semi-Pro Baseball to Dir of Engineering @ BetterHelp, w Johnathan Brooks
08/29/2025
22: From Semi-Pro Baseball to Dir of Engineering @ BetterHelp, w Johnathan Brooks
Description: In this conversation, Bolaji and Johnathan "JB" Brooks discuss JB's journey from semi-pro baseball player to a data engineering leader at BetterHelp. They explore the balance between mental health and high-pressure environments, the importance of dbt and Kimball modeling in data engineering, and the evolving landscape of AI and machine learning. JB shares insights on communication skills, measuring the value of data work, and the significance of understanding stakeholders. The discussion emphasizes the need for empathy and personal connection in professional success, along with practical advice for aspiring data professionals. Takeaways: JB played semi-pro baseball and has a passion for mental health. The pressure of perfection can lead to mental health challenges. Mental health awareness is crucial in high-pressure environments. JB's career began in the insurance industry before transitioning to data engineering. He adopted dbt early on, recognizing its potential in data transformation. Machine learning and AI are rapidly evolving fields in data engineering. BetterHelp's mission aligns with JB's values and career goals. Communication skills are essential for data professionals to convey value. Understanding stakeholders is key to being a valuable data professional. Professional success should be defined by personal values, not external expectations. Chapters: 00:00: Introduction to JB's Journey 06:09: Mental Health Awareness in High-Pressure Environments 09:09: JB's Career Beginnings in Insurance 10:33: Early Exposure to DBT and Data Engineering 11:24: Transitioning to Solutions Architect 13:18: Navigating the Data Engineering Landscape 19:49: Interview Insights and Lessons Learned 21:49: Joining BetterHelp and Work-Life Balance 24:21: The Impact of AI on Human Productivity 26:51: The Importance of Human Connection in Tech 27:41: Understanding Kimball Dimensional Modeling 29:46: Modern Applications of Kimball Modeling 31:21: Challenges and Pitfalls of Kimball Modeling 36:58: Team Structure and Collaboration in Data 37:55: Data Disasters and Lessons Learned 39:38: Proud Projects and Their Impact 40:58: Measuring the Value of Data Work 42:56: Honing Communication and Persuasion Skills 46:09: Defining Professional Success 50:55: Encouragement for Emerging Data Professionals Speakers: Guest: , former Director of Data Engineering at BetterHelp. (Now Principal Data & AI Architect at Astrodata) Host: , Community Manager at dbt Labs We’re Building the Future of Data. Together. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi—
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21: From Optimizing Physical Warehouses, to Optimizing FinOps Data Warehouses: Eddy Zulkifly
08/28/2025
21: From Optimizing Physical Warehouses, to Optimizing FinOps Data Warehouses: Eddy Zulkifly
Description: In this episode of Data Career Transformations, Bolaji interviews Eddy Zulkifly, a senior staff data engineer at Kanaxis. They discuss Eddy's journey from chemical engineering to data engineering, his passion for soccer coaching, and the importance of community and mentorship in professional growth. Eddy shares insights on the role of Excel in business, the challenges of FinOps, and the significance of a growth mindset in both sports and data careers. He emphasizes the value of learning in public and encourages data professionals to share their experiences and learn from one another. Takeaways Eddy transitioned from chemical engineering to industrial engineering due to his interest in psychology and data analysis. Excel remains a crucial tool in business, often seen as the universal data language. Eddy's experience in supply chain management has greatly influenced his approach to data engineering. Coaching kids in soccer has taught Eddy the importance of tailoring strategies to individual needs. The concept of learning in public can accelerate personal and professional growth. Eddy believes in the importance of mentorship and community support in the data field. Understanding business requirements is key to effective data engineering. Eddy's team at Kanaxis is structured to promote collaboration across data lifecycle stages. Technical challenges in FinOps often involve cost allocation and resource tagging. Eddy aspires to lead a data team and build impactful data products in the future. Chapters 00:00 Introduction to Data Career Transformations 02:47 Culinary Adventures in Malaysia and Singapore 05:41 The Joy of Coaching Soccer 08:29 From Chemical to Industrial Engineering 11:08 The Role of Excel in Business 13:51 Transitioning to Data Engineering 16:44 Understanding Kanaxis and Its Operations 19:23 The Structure of the Data Team at Kanaxis 22:12 Challenges in FinOps and Data Optimization 22:22 Navigating FinOps Challenges 25:12 Lessons from the Pandemic: Data Engineering at Home Depot 28:25 Proud Projects: Implementing Modern Data Stacks 30:52 Mentorship and Community in Data Engineering 34:12 Growth Mindset: Coaching and Learning 39:42 Future Aspirations in Data Engineering 41:46 Advice for Data Professionals Speakers: Guest: , Senior Staff Data Engineer, Kinaxis Host: , Community Manager at dbt Labs We’re Building the Future of Data. Together. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi—
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20: From Data Science & Engineering, to AI & ML Solutions Architect: Louis Guitton
08/26/2025
20: From Data Science & Engineering, to AI & ML Solutions Architect: Louis Guitton
Description: In this episode, Bolaji interviews Louis Guitton, an engineering leader with extensive experience in data engineering and analytics. They discuss Louis's journey from sports to data, his experiences at One Football Labs, and the challenges of communicating technical concepts to non-technical stakeholders. Louis shares insights on handling stress and burnout, measuring the impact of data projects, and the importance of sustainable personal growth in a rapidly evolving field. He emphasizes the need for data professionals to understand the business context and offers valuable advice for those looking to build a fulfilling career in data. Subscribe on: | | | Takeaways Louis has a diverse background in sports and data. He emphasizes the importance of mental and physical preparation for marathons. Data analytics is becoming increasingly important in sports. Louis's career journey includes freelancing and working at One Football Labs. He faced challenges in building a tagging system for football content. Communication with non-technical stakeholders is crucial for data professionals. Burnout is a common issue in the tech industry, and it's important to address it. Measuring the impact of data projects can be challenging but necessary. Sustainable personal growth is key to a long-term career in data. Understanding the business context is essential for data professionals. Chapters 00:00 Introduction to Data Career Transformations 01:51 The Intersection of Sports and Data 05:22 The Role of Data in Personal Health 0 7:56 Career Journey: From Engineering to Freelancing 11:05 Building a Data-Driven Business Unit 17:26 Tackling Technical Challenges in Data Engineering 20:49 Shipping the First Version: Lessons Learned 21:33 Communicating with Non-Technical Stakeholders 24:11 The Importance of Domain Knowledge 26:35 Handling Stress and Burnout in Data Careers 30:12 Measuring Impact in Data Projects 33:14 Sustainable Personal Growth in Data Careers 37:51 Mentorship and Influences in Career Development 38:45 Advice for Building a Fulfilling Career Speakers: Guest: , AI Solutions Architect and ML Engineer Host: , Community Manager at dbt Labs We’re Building the Future of Data. Together. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi—
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24: From Ballet Mech Engineer, to HR Tech Data Engineer: Larissa Mendes
08/01/2025
24: From Ballet Mech Engineer, to HR Tech Data Engineer: Larissa Mendes
In this episode, Bolaji Oyejide interviews Larissa Mendes, a Level 3 Data Engineer at Gupy, who shares her unique journey from mechanical engineering to data engineering. Larissa discusses her experiences with data quality challenges, the importance of community support, and her current tech stack at Gupy. She also provides valuable insights on overcoming interview challenges and the significance of effective communication with stakeholders. Larissa emphasizes the need for continuous learning and the power of networking in advancing one's career in data. Takeaways: Larissa transitioned from mechanical engineering to data engineering by exploring her interest in programming. She faced challenges during her first technical interview but learned to move on from questions she couldn't answer. Building reliable data pipelines is a key aspect of her role as a data engineer. Data quality issues can significantly impact client trust and require careful management. Effective communication with stakeholders is crucial for delivering value through data. Larissa emphasizes the importance of community support for career growth in data. She encourages aspiring data professionals to find their passion and connect with like-minded individuals. Continuous learning and adapting to new technologies are essential in the data field. Larissa's proudest project involved migrating critical queries to dbt, improving developer experience. Networking and learning from others can enhance one's skills and career opportunities. Chapters: 00:00 Introduction to Larissa Mendes and Her Journey 05:48 From Mechanical Engineering to Data Engineering 12:32 The Transition to Data Engineering 17:33 Navigating Technical Interviews 19:57 Lessons Learned and Advice for Aspiring Data Engineers 20:35 Building Confidence in Professional Environments 21:34 Exploring the Tech Stack at Guppy 23:20 The Power of dbt in Data Engineering 24:51 Team Dynamics and Roles in Data Engineering 26:45 Learning from Data Disasters 29:23 Communicating Data Value to Stakeholders 31:34 Managing Stakeholder Expectations 34:12 Empathy in Data Requests 36:48 Proud Projects in Data Engineering 40:18 Advice for Advancing in Data Careers Speakers: Guest: , Data Engineer II at Gupy Host: , Community Manager at dbt Labs We’re Building the Future of Data. Together. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi—
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19: From Quantum Physicist to Roche Head of Engineering? Yannick Misteli
07/28/2025
19: From Quantum Physicist to Roche Head of Engineering? Yannick Misteli
In this episode, Bolaji interviews Yannick Misteli, head of engineering at Roche, who shares his unique journey from a PhD in quantum physics to a leadership role in data science. Yannick discusses his early experiences in finance, the importance of building a solid data organization, and the balance between people, process, and technology. He emphasizes the significance of trust in data relationships and offers insights into managing stress and communicating business value. The conversation also touches on his passion for dance and how it has shaped his personal and professional life. Subscribe on: | | | Takeaways: Yannick's journey from quantum physics to data science showcases the importance of diverse experiences. Building a data organization requires a focus on people, process, and technology. Trust is essential in data relationships and impacts business outcomes. Early career experiences in finance provided valuable insights into data use cases. Transitioning from academia to industry involves learning to speak the business language. Yannick emphasizes the importance of a solid foundation in any career. Data testing is crucial for building trust with stakeholders. Effective communication of business value is a key skill for data leaders. Maintaining a work-life balance is important for long-term success. Mentorship and continuous learning are vital for career growth. Chapters: Introduction to Yannick's Journey The Unexpected Path to Dance From Quantum Physics to Data Science Transitioning from Academia to Industry Consulting Experience and Its Impact Personality and Career Fit in Data Roles The Triad of People, Process, and Technology People, Process, and Technology: The Triad of Success Climbing the Corporate Ladder: Yannick's Journey The Role of dbt in Data Transformation Learning from Data Disasters: The Importance of Testing Communicating Business Value: The Data Leader's Challenge Managing Stress: Balancing Work and Life Mentorship and Inspiration: Learning from Others Advice for Aspiring Data Professionals: Building a Foundation Speakers: Guest: , Head of Engineering, Global Pharma Strategy, Roche Host: , Community Manager at dbt Labs Building in Public: The Best Way to Learn Data. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi—
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18: From CFO to Data Engineer? Philip Boontje
07/10/2025
18: From CFO to Data Engineer? Philip Boontje
In this episode of Data Career Transformations, Bolaji interviews Philip Boontje, a finance executive and data architect. Philip shares his unique journey from chemical engineering to finance and ultimately to data engineering. He discusses the challenges and successes he has faced in his career, including the transition from spreadsheets to data engineering, the discovery of dbt, and the importance of building a strong data architecture. The conversation also touches on the future of data with semantic layers and AI, as well as the importance of mental health and work-life balance in the fast-paced world of data engineering. Philip offers valuable advice for aspiring data professionals and emphasizes the need for creativity and interdisciplinary skills in the field. Subscribe on: | | | Takeaways: Philip's journey from chemical engineering to finance and data architecture showcases the importance of interdisciplinary skills. The transition from spreadsheets to data engineering is crucial for scaling businesses effectively. Discovering dbt transformed Philip's approach to data management and engineering. MaxQ Analytics focuses on providing data architecture solutions for companies that need support in data engineering. Building strong client relationships is essential for successful project management in data engineering. Data disasters often stem from unreliable source systems and the challenges of maintaining data integrity. Success in data engineering is often invisible; clients appreciate when things run smoothly without issues. The semantic layer is key to creating a single source of truth in data management. AI and analytics agents will play a significant role in the future of data engineering. Maintaining mental health and work-life balance is crucial in the fast-paced world of data engineering. Chapters: 00:00: Introduction to Data Career Transformations 03:58: Philip's Unique Journey from Engineering to Finance 10:33: Transitioning from Spreadsheets to Data Engineering 13:07: Discovering the Power of dbt 18:18: MaxQ Analytics: Bridging the Data Gap 22:10: Overcoming Data Challenges and Technical Struggles 23:09: The Challenges of Data Engineering 24:52: Understanding the Semantic Layer 26:54: The Future of Data Interaction with AI 28:21: The Role of Data Engineers in an AI World 31:40: Managing Stress and Burnout in Data Careers 33:46: Success Stories in Data Engineering 35:55: Measuring the Impact of Data Work 38:17: Mentorship and Career Advice for Data Professionals 40:20: Vision for the Future of Data Engineering Speakers: Guest: , MaxQ Analytics Data Engineer & Guild Lead Host: , Community Manager at dbt Labs We’re Building the Future of Data. Together. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi—
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17: From Psychology to Analytics Engineering: Juan Manuel Perafan
07/09/2025
17: From Psychology to Analytics Engineering: Juan Manuel Perafan
In this episode, Bolaji interviews Juan Manuel Perafan, a psychology major turned analytics engineer, who shares his journey from Colombia to the Netherlands and his transition into the data field. They discuss the importance of networking, the challenges of imposter syndrome, and the evolving role of analytics engineering. Juan emphasizes the value of being replaceable in a job and offers advice for aspiring data professionals, highlighting the significance of foundational skills and the need to stay adaptable in a rapidly changing industry. Subscribe on: | | | Takeaways: Juan transitioned from psychology to data due to market competition. Networking is crucial for career opportunities in data. Imposter syndrome is common in tech; focus on your unique value. Being replaceable can free you to explore new opportunities. Foundational skills like SQL and stakeholder management are essential. Cultural differences can impact communication in professional settings. Early adoption of new technologies can shape your career. It's important to clarify job roles to avoid confusion. Passion for data can help sustain a long-term career. Meetups can foster valuable connections and collaborations. Chapters: 00:00: Introduction to Juan Manuel Perafan 02:47: Cultural Insights and Relationship Dynamics 05:14: Career Transition from Psychology to Data 07:50: The Journey into Data Engineering 10:18: The Emergence of Analytics Engineering 12:53: Networking and Community Engagement 15:22: Cultural Differences in Professional Relationships 21:45: Navigating Cultural Differences in Communication 22:56: The Importance of Passion in Tech Careers 25:09: The Evolution of dbt in Tech Stacks 28:25: Understanding and Overcoming Imposter Syndrome 31:53: The Balance of Being Replaceable vs. Irreplaceable 34:57: The Value of Early Adoption in Technology 39:55: Advice for Aspiring Data Professionals Speakers: Guest: , Co-Author, Fundamentals of Analytics Engineering Host: , Community Manager at dbt Labs We’re Building the Future of Data. Together. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi—
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16: From Yale Rugby & Jazz, to Data FinTech & AdTech? Sr Dir of Analytics, Bryan Herbert
07/08/2025
16: From Yale Rugby & Jazz, to Data FinTech & AdTech? Sr Dir of Analytics, Bryan Herbert
In this episode of Data Career Transformations, Bolaji interviews Bryan Herbert, Senior Director of Analytics at Kargo. They discuss Bryan's unique career path from electrical engineering to fintech and ad tech, exploring how he applies his diverse experiences to build effective data teams. Bryan shares insights on the importance of team dynamics, the data maturity curve, and the future of business intelligence, emphasizing the need for low ego and high empathy in data professionals. He also provides valuable advice for aspiring data analysts and engineers, highlighting the significance of practical experience and understanding stakeholder needs. Takeaways: Bryan's journey from electrical engineering to data analytics showcases the diverse paths into the data field. Building a successful data team is akin to forming a jazz band, requiring a mix of personalities and skills. Data maturity is crucial for organizations to effectively leverage their data for business impact. The future of business intelligence may involve more intuitive interactions with data, such as conversational interfaces. Low ego and high empathy are essential traits for data professionals to effectively collaborate with stakeholders. Practical experience, such as personal projects, can significantly enhance a candidate's appeal in the job market. Understanding the business context and stakeholder needs is vital for data professionals to deliver impactful insights. The data maturity curve consists of descriptive, predictive, prescriptive analytics, and automation stages. Effective communication of data projects' business impact is essential for gaining stakeholder support. Continuous learning and adaptation are key in the rapidly evolving field of data analytics. Chapters: : Introduction to Data Career Transformations : The Musical Journey: Jazz Trumpet to Data : Building Teams: The Jazz Band Analogy : Rally: Fractional Ownership of Collectibles : The Role of Data in Unique Asset Valuation : Transitioning from Rally to Cargo : Navigating the Ad Tech Landscape : The Importance of Domain Knowledge in Data : Team Structure and Cross-Pollination of Ideas : Exploring Rugby: A Unique Sport The Scrum: Teamwork in Rugby and Agile : Understanding the Data Maturity Curve : The Future of Business Intelligence : Building Skills for Data Professionals Speakers: Guest: Bryan Herbert, Sr Director of Analytics @ Kargo Host: Bolaji Oyejide, Community Manager at dbt Labs We’re Building the Future of Data. Together. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi—[]
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15: From Biochemist to Analytics Engineering Mgr @ Hubspot: Nicholas Yager
07/07/2025
15: From Biochemist to Analytics Engineering Mgr @ Hubspot: Nicholas Yager
In this episode of Data Career Transformations, Bolaji speaks with Nicholas Yager, the Analytics Engineering Manager of Enterprise Data Platform, at HubSpot. They discuss Nicholas's journey from biochemistry to data engineering, his experiences at dbt Labs, and the importance of creative collaboration in data. Nicholas shares insights on navigating career paths, the challenges of scaling data engineering, and the role of dbt in solving data problems. Nicholas emphasizes the myth of the objective in career development and the importance of negotiation in meeting deadlines. The conversation concludes with Nicholas's aspirations for the future in building tools that enhance the data engineering experience. Takeaways: Nicholas Yager emphasizes the importance of creative collaboration in data engineering. He believes that most deadlines are lies and should be viewed as negotiations. Nicholas's journey from biochemistry to data engineering showcases the diverse paths into the field. He highlights the significance of dbt in managing data solutions effectively. The conversation touches on the challenges of scaling data engineering in large organizations. Nicholas advocates for a growth mindset and the value of professional curiosity. He shares insights on the importance of intrinsic motivation in team dynamics. Nicholas's experiences illustrate the need for adaptability in career paths within data. He expresses a desire to build tools that make data engineering delightful. The discussion emphasizes the iterative nature of data work and the need for continuous improvement. Speakers: Guest: Nicholas Yager, Analytics Engineering Manager, Enterprise Data Platform, Hubspot Host: Bolaji Oyejide, Community Manager at dbt Labs We’re Building the Future of Data. Together. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi—[] Chapters: 00:00: Introduction to Data Career Transformations 02:00: Journey to dbt Labs and HubSpot 04:39: From Biochemistry to Data Engineering 09:26: The Myth of the Objective 11:46: Creative Collaboration in Data 14:14: Understanding Roles in Data 17:54: Team Structure at HubSpot 20:15: Challenges of Scaling Data Projects 22:50: The Gardener's Approach to Data Management 24:06: Building Data Habits Early 26:08: Tech Stack Insights 29:26: The Journey with DBT 30:05: Data Disaster Stories 34:53: Handling Stress in Data 37:28: Negotiating Deadlines 41:36: Empowering Team Ownership 44:22: Future Aspirations in Data
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14: From Marine Biologist to Sr Data Engineer at Shopify: Elize Papineau
06/04/2025
14: From Marine Biologist to Sr Data Engineer at Shopify: Elize Papineau
In this episode, Bolaji interviews Elize Papineau, a senior data engineer at Shopify, who shares her unique journey from marine biology to data engineering. Elize discusses her eclectic background, the challenges of finding the right job title in data, and the importance of continuous learning. She highlights her experiences at dbt Labs and Shopify, the significance of data governance, and the value of mentorship. Elize also reflects on her proudest projects, the lessons learned from data disasters, and her aspirations for community involvement in the data field. Takeaways: Elize transitioned from marine biology to data engineering through a gradual process of learning and adaptation. Finding the right job title in data can be challenging, and understanding one's strengths is crucial. Continuous learning and practical experience are key to career growth in data. Elize emphasizes the importance of community and mentorship in the data field. Data governance and stakeholder interaction are critical in large organizations like Shopify. Elize's proudest projects are those that see high user adoption and utility. Data disasters can provide valuable lessons and insights for future work. Interview challenges often reveal the importance of problem-solving and communication skills. Elize aims to contribute to the data community and support others in their journeys. Measuring the impact of data work involves understanding user needs and ensuring timely access to data. Chapters: : Introduction to Elize Papineau : Elize's Unique Background and Skills : Transition from Marine Biology to Data Engineering : Navigating the Data Job Market : Finding Identity in Data Roles : Continuous Learning and Skill Development : The Importance of Practical Experience : Discovering dbt and Its Impact : Working at Shopify and Personal Insights : Iced Tea: A Lifestyle Choice : Data Challenges at Shopify : Understanding Stakeholders and Their Needs : Data Disasters: Learning from Mistakes : Navigating Tough Interview Questions : Proud Projects and Their Impact : Measuring Business Impact : Influences and Mentorship in Data 47:38: Future Aspirations in the Data Community Speakers: Guest: is a Senior Data Engineer at Shopify. Host: is the community manager at dbt Labs, and host of Data Career Transformations. — About the dbt Community: We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. dbt Community - for and by data pros. Build reliable transformation pipelines. Test & deploy models. Optimize queries. Structure data for self-serve analysis. Come hang out and transform with 70,000 of the brightest Analytics Engineers, Data Engineers, Data Analysts, and Data Scientists in the world 👉 Subscribe on: | | |
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13: From SW Intern to Chick-Fil-A Sr Lead Data Engineer: Tim Castillo
06/02/2025
13: From SW Intern to Chick-Fil-A Sr Lead Data Engineer: Tim Castillo
In this episode of Data Career Transformations, Bolaji Oyejide interviews Tim Castillo, a senior lead data engineer at Chick-fil-A. Tim shares his journey from software engineering to data engineering, emphasizing the importance of operational efficiency and the role of data in enhancing customer experiences. He discusses the challenges of stakeholder communication, the significance of building trust, and the balance between maintenance and innovation in data projects. Tim also highlights the value of tools like dbt in streamlining data processes and shares insights on measuring the impact of data work. Throughout the conversation, Tim advocates for lifting the floor while extending the ceiling in data practices, ensuring a solid foundation for future growth. Takeaways: Tim believes in scaling organizations by lifting the floor while extending the ceiling. Data engineering plays a crucial role in enhancing operational efficiency at Chick-fil-A. Tim's career journey includes roles in software engineering and data engineering. He emphasizes the importance of asking questions to understand stakeholder needs. Tim advocates for using tools like dbt to streamline data processes. He shares lessons learned from transitioning to data engineering. Tim highlights the significance of stakeholder communication and empathy. Measuring impact in data roles can be challenging but focuses on joy and efficiency. Tim encourages early-career professionals to balance learning tools with foundational skills. He believes in the importance of building trust as a data professional. Chapters: : Introduction to Tim Castillo and Chick-fil-A : The Role of Data in Location Strategy : Operational Efficiency and Intentionality at Chick-fil-A : Tim's Career Journey: From Software Engineer to Data Engineer : The Importance of Side Projects and Learning : The Evolution of Tim's Role in Data : Understanding Data Engineering vs. Data Science : Raising the Floor While Extending the Ceiling : Raising the Ceiling and Floor in Data Work : Team Structure and Scaling Challenges : The Role of dbt in Data Engineering : Learning from Data Disasters : Effective Stakeholder Communication 43:04: Measuring Success in Data Roles 47:34: Advice for Early-Career Data Professionals Speakers: Guest: Tim Castillo, Senior Lead Data Engineer at Chick-Fil-A Host: Bolaji Oyejide, Community Manager at dbt Labs — About the dbt Community: We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. dbt Community - for and by data pros. Build reliable transformation pipelines. Test & deploy models. Optimize queries. Structure data for self-serve analysis. Come hang out and transform with 70,000 of the brightest Analytics Engineers, Data Engineers, Data Analysts, and Data Scientists in the world
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12: From Customer Support to RevOps Analytics @ 1Password: Nate Sooter
05/22/2025
12: From Customer Support to RevOps Analytics @ 1Password: Nate Sooter
In this episode of the Data Career Transformations Show, Bolaji interviews Nate Sooter, a data professional who shares his unique journey from customer support to becoming a manager of Revenue Operations and Analytics at 1Password. Nate discusses the diverse paths into analytics careers, the importance of domain knowledge, and the challenges of navigating the 'great filter' in data jobs. He emphasizes the significance of networking, building relationships, and understanding the business context to succeed in data roles. Nate also reflects on his experiences at Smartsheet, the evolution of the tech stack, and the lessons learned from data disasters. He concludes with advice for aspiring data professionals and shares his future aspirations in leadership. Chapters: : Introduction to Data Career Transformation : The Wandering Path to Analytics : The Great Filter in Data Careers : Non-Traditional Steps to Break Through : Taking a Chance on Analytics : Preparation Meets Opportunity : Navigating Career Paths in Data : The Evolution of Data Teams : Tech Stack Transformation at Smartsheet : Community and Networking in Data : Learning from Data Disasters : Building Trust Through Accountability : Lessons in Data Integrity : Proud Moments in Data Solutions : Measuring Impact in Data Teams : Advice for Aspiring Data Professionals Takeaways: There's no single clear path into an analytics career. Networking is crucial for career growth in data. Understanding the business context is key for data professionals. Building domain knowledge can differentiate you in analytics roles. Entry-level professionals should seek to be strategic partners, not just ticket takers. Data teams must focus on providing value to stakeholders. Trust is the currency of a successful data team. Mistakes in data can lead to loss of trust; it's important to have checks in place. Creating solutions that are used by many is a significant achievement. Continuous learning and adaptation are essential in the data field. Speakers: Guest: Add LinkedIn links for the guest Host: is the community manager at dbt Labs, and host of Data Career Transformations. — About the dbt Community: We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. dbt Community - for and by data pros. Build reliable transformation pipelines. Test & deploy models. Optimize queries. Structure data for self-serve analysis. Come hang out and transform with 70,000 of the brightest Analytics Engineers, Data Engineers, Data Analysts, and Data Scientists in the world
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11: From Soul-Sucking Telecom Presales, to Data Engineering Mgr: Jessica Franks
05/14/2025
11: From Soul-Sucking Telecom Presales, to Data Engineering Mgr: Jessica Franks
In this episode, Bolaji interviews Jessica Franks, a data engineering manager at Not On The High Street, who shares her unique journey from telecom engineering to data leadership. Jessica discusses her transition to the UK, the challenges of managing a data team, and the importance of communication and mentorship in the data field. Jessica also explains the significance of data strategy, the use of Wardley mapping, and how she measures the impact of her work. Jessica emphasizes the need for continuous learning and adapting in the evolving data landscape, and her aspirations for the future in data leadership. Speakers: Guest: is the Data Engineering Manager at Not On the High Street, an eCommerce company based in the United Kingdom Host: is the community manager at dbt Labs, and host of Data Career Transformations. Takeaways: Jessica's journey from telecom to data leadership is unique and inspiring. Taking time off to study data science can lead to career transformation. Communication skills are crucial for data professionals. Wardley mapping is a valuable tool for visualizing data strategy. The modern data stack includes tools like Snowflake and dbt. Measuring impact in data work can be challenging but rewarding. Mentorship and community support are vital in the data field. Learning to say no is important for managing workload. Data maturity assessments can guide strategic decisions. Continuous learning is essential in the evolving data landscape. Chapters: : Introduction to Jessica's Journey : From Telecom to Data Leadership : The Transition to Data Science : Navigating Career Changes : First Day at Not On The High Street : Building a Data Team : Creating a Data Strategy : The Importance of Communication in Data : Implementing Wardley Mapping : Modern Data Stack at Not On The High Street : The Value of dbt in Data Engineering : Change Management in Data Teams : Understanding Data Maturity : The Importance of Community and Mentorship : Asking Questions and Overcoming Hesitation : Handling Stress and Conflicting Priorities : Learning to Say No : Balancing Maintenance and Innovation : Measuring Impact in Data Roles : Future Aspirations in Data Leadership — About the dbt Community: We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. dbt Community - for and by data pros. Build reliable transformation pipelines. Test & deploy models. Optimize queries. Structure data for self-serve analysis. Come hang out and transform with 70,000 of the brightest Analytics Engineers, Data Engineers, Data Analysts, and Data Scientists in the world
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10: From Sys Admin Skateboards to Effective Data Products, with Ash Smith
05/14/2025
10: From Sys Admin Skateboards to Effective Data Products, with Ash Smith
In this episode of Data Career Transformations, Bolaji interviews Ash Smith, a seasoned data professional with a diverse background in various industries including education, health, online gaming, and mining. Ash shares his journey into the data field, the evolution of data roles, and the importance of data products. He discusses the challenges faced by data teams, the significance of networking, and how to measure the impact of data work. Ash emphasizes the need for curiosity, collaboration, and effective data storytelling in the data profession, while also providing valuable advice for aspiring data professionals. Speakers: Guest: is the Manager of Data Platform at South32, a Mining company in Perth, Australia Host: is the community manager at dbt Labs, and host of Data Career Transformations. --- Takeaways: Ash Smith has a diverse background in data across multiple industries. Data products are essential for delivering value to businesses. Networking is crucial for career growth in the data field. Curiosity and asking questions are key traits for data professionals. Data storytelling is a vital skill for communicating insights. The data industry needs a consistent framework for success. Building effective data teams requires collaboration and governance. Measuring the impact of data work can be complex and subjective. Data professionals should focus on foundational skills and continuous learning. Engaging with the community through meetups and conferences is beneficial. Sound Bites: "Data products can change the way we work." "Always be curious and ask questions." "Data storytelling is a crucial skill." Chapters: : Introduction to Ash Smith and His Journey : Ash's Current Role in Mining Data : Career Path and Transition to Data : Breaking into Online Gaming and Data Roles : Early Interests in Data and Patterns : Understanding Data Products : Evolving Data Practices and Challenges : Day-to-Day in Data Management : Navigating Data Disasters : Handling Stress and Burnout : The Challenge of Ad Hoc Requests : Celebrating Project Successes : Influences and Mentorship in Career : Building Relationships for Career Growth : Measuring Impact in Data Work : Technology's Role in Data Management : Advice for Aspiring Data Professionals — About the dbt Community: We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. dbt Community - for and by data pros. Build reliable transformation pipelines. Test & deploy models. Optimize queries. Structure data for self-serve analysis. Come hang out and transform with 70,000 of the brightest Analytics Engineers, Data Engineers, Data Analysts, and Data Scientists in the world
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9: From Actuary to Analytics Engr Mgr @ Hubspot. Kasey Mazza
05/09/2025
9: From Actuary to Analytics Engr Mgr @ Hubspot. Kasey Mazza
In this episode of Data Career Transformations, Bolaji interviews Kasey Mazza, an analytics engineering manager at HubSpot. Kasey shares her journey from actuarial science to analytics engineering, emphasizing the importance of merging technical skills with emotional intelligence. She discusses her approach to career growth modeled after the software development life cycle, her day-to-day responsibilities, and the significance of building teams like a community. Kasey also highlights the challenges of data management, the importance of fostering a learning culture, and how to measure the impact of data roles. Throughout the conversation, she offers valuable insights and advice for aspiring data professionals. --- Speakers: Guest: is the Director of Analytics Engineering at Hubspot Host: is the community manager at dbt Labs, and host of Data Career Transformations. --- About the dbt Community: Building in Public: The Best Way to Learn Data. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi— Takeaways: Kasey transitioned from actuarial science to analytics engineering. She emphasizes the importance of emotional intelligence in data roles. Career growth can be modeled after the software development life cycle. Building teams like a community fosters collaboration and innovation. Kasey advocates for a learning culture within data teams. Measuring impact in data roles can be challenging but is essential. Cross-functional collaboration is key to successful projects. Kasey encourages following curiosity and passion in career paths. She believes in collecting skills rather than just chasing titles. Kasey reads extensively, averaging 110 books a year. Chapters: : Introduction to Kasey Mazza and Her Journey : Kasey's Data Origin Story : Applying the Software Development Life Cycle to Career Growth : The Role of an Analytics Engineering Manager : Building Data Teams Like a Community : Team Structure and Roles : Tech Stack and Tools Used : Data Challenges and Communication Gaps : Shaping Team Culture and Shared Language : Cultivating a Learning Culture : Investing in Personal Development : Beyond Titles: Collecting Skills : The Power of Reading : Building a Customer Score : Measuring Impact in Data : Defining Professional Success : The Influence of Mentorship : Looking Ahead: Future Aspirations : Advice for Aspiring Data Professionals
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8: From Law School to Nigeria's FinTech Data Chef? Damola Onabanjo
05/07/2025
8: From Law School to Nigeria's FinTech Data Chef? Damola Onabanjo
In this episode of Data Career Transformations, Bolaji interviews Damola Onabanjo, a business intelligence manager at Kuda, who shares her unique journey from an international law graduate to a data professional. The conversation covers her love for cooking shows, her role at Kuda, the transition from law to data, the importance of mentorship, and the challenges faced in the data industry. Damola emphasizes the significance of passion, collaboration, and knowledge sharing in building a successful data career. Takeaways: Damola transitioned from law to data analytics after realizing her passion for problem-solving. Kuda aims to bring banking to the doorstep of every Nigerian, offering various financial products. The importance of mentorship in navigating a data career is crucial for growth. Damola emphasizes the need for passion to sustain interest in data work. She discovered dbt as a tool that transformed her data workflow. Handling data disasters requires effective communication and negotiation with stakeholders. Building a collaborative team culture is essential for knowledge sharing and growth. Damola encourages aspiring data professionals to seek mentorship and guidance. She believes in under-promising and over-delivering to manage stakeholder expectations. Damola finds joy in mentoring others and helping them grow in their data careers. Chapters: : Introduction to Damola Onabanjo : The Journey to Business Intelligence : Understanding Kuda and Its Impact : Transitioning from Law to Data : Building a Career in Data Analytics : Navigating the Data Landscape : The Role of Personality in Data Careers : Exploring Data Roles and Responsibilities : Discovering dbt and Its Benefits : Discovering dbt and Building Skills : Navigating Data Disasters : Managing Stakeholder Expectations : The Art of Delegation : Fostering Team Collaboration : Building a Knowledge-Sharing Culture : Mentorship and Personal Growth : Advice for Aspiring Data Professionals Speakers: Guest: is the Business Intelligence Manager at Kuda Host: is the community manager at dbt Labs, and host of Data Career Transformations. — About the dbt Community: We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. dbt Community - for and by data pros. Build reliable transformation pipelines. Test & deploy models. Optimize queries. Structure data for self-serve analysis. Come hang out and transform with 70,000 of the brightest Analytics Engineers, Data Engineers, Data Analysts, and Data Scientists in the world. 👉
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7: From Clown School to Director of Analytics: Wade Wachs
04/30/2025
7: From Clown School to Director of Analytics: Wade Wachs
In this episode of The Data Career Transformations Show, Bolaji interviews Wade Wachs, the Director of Information and Analytics at Liquid Web. Wade shares his unique journey from juggling and clown school to building a data-driven culture in a web hosting company. The conversation explores the evolution of data roles, the challenges of self-service data, and the importance of mentorship in the data field. Wade emphasizes the need for data professionals to understand the business context behind their work and to be proactive in shaping data requests rather than just fulfilling them. The episode concludes with insights on celebrating data successes and the value of strong mentorship in career development. Takeaways: Wade's unique background in juggling and clown school adds a fun twist to his data career. The evolution of Liquid Web's data culture reflects the importance of data-driven decision-making. Understanding the web hosting industry is crucial for effective data analytics. Transitioning into data roles can be a journey filled with learning and adaptation. The role of a Director of Information and Analytics involves diverse responsibilities and challenges. Building a data team requires careful consideration of roles and dynamics. Self-service data can be both empowering and challenging for organizations. Data ownership is essential for driving business outcomes. dbt plays a significant role in modern data transformation processes. Data disasters often stem from miscommunication and technical issues, highlighting the need for clear processes. Sound Bites: "Those who know will always work for those who know why." "Be so good they can't ignore you." "Don't be an order taker, be an order shaper." "I fell in love with SQL." "Self-serve is a myth." "A bad join can cost millions." Chapters: :Introduction to Data Careers and Juggling : Wade's Journey into Data and Web Hosting : Transitioning to a Data-Driven Culture : The Evolution of Data in Web Hosting : Wade's Data Career and Love for SQL : Role of an Analytics Engineer : Day-to-Day Responsibilities of a Data Director : Team Structure and Data Engineering Challenges : Self-Service Data and Executive Needs : The Role of dbt in Data Transformation : The Evolution of Data Engineering : Navigating Data Disasters : The Importance of Domain Knowledge : Learning from Mistakes : Handling Stress and Expectations : Mentoring the Next Generation : Proud Moments in Data Projects About the dbt Community: We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. dbt Community - for and by data pros. Build reliable transformation pipelines. Test & deploy models. Optimize queries. Structure data for self-serve analysis. Come hang out and transform with 70,000 of the brightest Analytics Engineers, Data Engineers, Data Analysts, and Data Scientists in the world
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6: From Pastry Chef to Head of Data at dbt Labs? Erica Louie.
04/23/2025
6: From Pastry Chef to Head of Data at dbt Labs? Erica Louie.
In this engaging conversation, Erica Louie shares her unique journey from aspiring pastry chef to Head of Data at dbt Labs, with host Bolaji Oyejidehighlighting the importance of empathy and communication in the data field. Erica discusses the skills and milestones that helped him climb the career ladder, the challenges of hiring for data roles, and the often thankless nature of data work. Erica also opens up about a personal failure that taught her valuable lessons and reflects on the overwhelming nature of leadership, ultimately finding joy in managing her team. B olaji & Erica further delve into various themes surrounding self-awareness in career growth, the measurement of data team value, the benefits of Cloud CLI, the importance of the semantic layer, challenges in data governance, strategies for building a data team from scratch, and the balance between service-oriented and strategic projects. The discussion emphasizes the need for self-reflection, effective communication within teams, and the integration of data practices into business strategies. Takeaways: Being different can lead to unique career paths. Analytical skills can be built over time. Empathy is crucial in data roles. Communication is key in data work. Hiring should balance hard and soft skills. Data work can often feel thankless. Learning from failures is essential for growth. Leadership can be overwhelming but rewarding. It's important to prioritize team culture. Finding joy in work is vital for success. Self-awareness is crucial for career growth. Regular self-check-ins can prevent burnout. Measuring data team value can be linked to company initiatives. Cloud CLI simplifies version management and enhances productivity. The semantic layer promotes best practices in data reporting. Data governance is an evolving challenge for organizations. Building a data team requires understanding executive needs. A phased approach to data projects is recommended for new teams. Balancing service requests with strategic initiatives is essential. Effective communication with stakeholders is key to data team success. About the dbt Community: We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. dbt Community - for and by data pros. Build reliable transformation pipelines. Test & deploy models. Optimize queries. Structure data for self-serve analysis. Come hang out and transform with 70,000 of the brightest Analytics Engineers, Data Engineers, Data Analysts, and Data Scientists in the world
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5: From Video Gamer to Principal at Infinite Lambda: Michael Han
04/16/2025
5: From Video Gamer to Principal at Infinite Lambda: Michael Han
In this episode of The Data Career Transformations Show, Bolaji Oyejide interviews Michael Han, Head of Product at Infinite Lambda. Michael discusses his journey from finance to data science, the evolution of data roles, and the importance of effective communication and domain knowledge in the data field. Michael shares insights on the day-to-day responsibilities of a data leader, lessons learned from data disasters, and strategies for quantifying the impact of data work. In this conversation, Michael Han discusses the limitations faced by data analysts, emphasizing the importance of domain knowledge for career progression. He shares insights on building a data team from scratch, the impact of behavioral change in data practices, and the reality of self-service data. Michael also reflects on mentorship, professional success, and offers advice for aspiring data professionals, highlighting the need for niche expertise in the evolving data landscape. Takeaways Michael transitioned from finance to data analytics during a boom in the field. DBT has played a significant role in modern data engineering. Analytics engineering emerged as a distinct role with the rise of dbt. Effective communication with stakeholders is crucial for data professionals. Starting with conclusions can save time in stakeholder meetings. Quantifying the impact of data work is essential for recognition. Domain knowledge enhances the effectiveness of data professionals. Debugging often requires a return to the basics of data logic. Data roles have evolved significantly over the past decade. Collaboration between technical and non-technical teams is vital. There is a natural cap to progression for data analysts. Technical skills alone are not enough; domain knowledge is crucial. Data professionals can become defined by efficiency rather than impact. Building a data team from scratch can be a rewarding experience. Behavioral change in data practices can have a significant impact. Self-service data is not a complete solution; support is needed. Mentorship plays a key role in professional development. Professional success can be defined by interesting work and lifestyle balance. Aspiring data professionals should focus on domain knowledge first. Niche expertise can provide a competitive edge in the data field. About the dbt Community: We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. dbt Community - for and by data pros. Build reliable transformation pipelines. Test & deploy models. Optimize queries. Structure data for self-serve analysis. Come hang out and transform with 70,000 of the brightest Analytics Engineers, Data Engineers, Data Analysts, and Data Scientists in the world
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4: From Math Tutor & Barista, to Analytics Engineer & Analyst! Lauren Benezra & Paige Berry of dbt Labs
04/10/2025
4: From Math Tutor & Barista, to Analytics Engineer & Analyst! Lauren Benezra & Paige Berry of dbt Labs
n this engaging conversation, Bolaji, Lauren, and Paige explore their diverse journeys in the data analytics field, discussing their career paths, the accessibility of data science, and the importance of collaboration and communication within data teams. They share personal experiences with data disasters, technical challenges, and the ever-present imposter syndrome. The discussion also highlights the significance of mentorship, building trust in data, and the skills necessary for aspiring data professionals, culminating in reflections on future aspirations in their careers. Takeaways: Data analytics careers often start from unexpected backgrounds. SQL is a fundamental skill that is accessible to many. Imposter syndrome is common among data professionals. Collaboration and communication are key in data teams. Building trust in data requires rigorous testing and validation. Mentorship plays a crucial role in career development. Data disasters can lead to valuable lessons. Technical challenges often require continuous learning. Documenting achievements can help combat imposter syndrome. Future aspirations can include mentoring and skill development. Building in Public: The Best Way to Learn Data. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi—
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3: Sexiest Job in the 21st Century? Ope Fabiyi, Analytics Manager at Data Culture
03/11/2025
3: Sexiest Job in the 21st Century? Ope Fabiyi, Analytics Manager at Data Culture
In this episode of The Data Career Transformations Show, Bolaji interviews Opeyemi Fabiyi, an analytics manager and community leader in the data space. Opeyemi shares his journey into data, discussing how he discovered his passion for analytics and the various roles he has held in the industry. He emphasizes the importance of community, mentorship, and continuous learning in building a successful career in data. Opeyemi also shares insights into his day-to-day responsibilities, the challenges he has faced, and the successes he has achieved, including his role in establishing the dbt community in Lagos. The conversation concludes with Opeyemi's aspirations for the future and advice for aspiring data professionals. Takeaways: Opeyemi discovered data during his final year in university. He emphasizes the importance of community in data careers. Choosing a path in data often requires experimentation. Opeyemi enjoys the blend of technical and business aspects of analytics engineering. His day-to-day varies significantly between consulting and internal roles. Building infrastructure from scratch was a significant challenge for him. He measures success by the impact of his work on clients. Opeyemi values mentorship and has had many indirect mentors. He advises aspiring data professionals to start with fundamentals. Opeyemi aims to lead data teams and drive strategy in the future. Chapters: 00:00: Introduction to Data Careers Show 01:41: Opeyemi's Journey into Data 05:07: Choosing a Path in Data 07:47: Day-to-Day as an Analytics Manager 09:47: Internal vs Consulting Data Teams 13:53: Data Disasters and Challenges 15:38: Building a Recommendation Engine 16:36: Understanding Data Infrastructure and Attribution 20:42: The Emotional Intelligence in Marketing 23:14: Managing Stress and Burnout in Data Roles 29:48: Success Stories and Measuring Impact 32:01: Future Aspirations and Mentorship in Data Speakers: is an Analytics Engineer at Data Culture. is the community manager at dbt Labs, and host of Data Career Transformations. — We're Building the Future of Data. Together. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi—
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2: From Mobile Apps to Staff Engineer at Teads: Christophe Oudar
03/11/2025
2: From Mobile Apps to Staff Engineer at Teads: Christophe Oudar
Bolaji interviews Christophe Oudar, a Staff Software Engineer at Teads, who shares his journey in data engineering, the challenges he faced, and the successes he achieved. Christophe discusses the vibrant dbt community, his career progression from junior to staff engineer, and the importance of mentorship and continuous learning. He also delves into the technical challenges of data engineering, including performance optimization and data disasters, while highlighting a successful project that saved significant costs for his company. The conversation wraps up with insights on professional success and future aspirations in the field of data engineering. Takeaways: Christophe Oudar is a passionate software engineer specializing in backend and data engineering. The dbt community is vibrant and inclusive, providing valuable support. Starting as a junior backend engineer, Christophe has progressed to Staff Software Engineer. Data cleaning and selection are crucial tasks in data science. Performance optimization is a common challenge in data engineering. Christophe's project saved hundreds of thousands on data warehouse costs. Trust and feedback from peers are key measures of professional success. Proactive communication is essential for leadership and mentorship. Christophe aspires to reach the Principal level in his career. Maintaining and evolving built projects is a rewarding aspect of engineering. Host: is the community manager at dbt Labs, and host of Data Career Transformations. Chapters: 00:00: Introduction to Data Careers and Christophe Oudard 01:43: Christophe's Journey into Data Engineering 05:10: Evolution of Data Engineering Roles 09:40: Career Progression and Mentorship 12:21: Data Disasters and Technical Challenges 14:57: Common Misconceptions in Data Engineering 16:15: Team Dynamics and Collaboration at Teeds 18:16: Managing Stress and Burnout in Data Roles 19:49: Success Stories and Project Achievements 21:47: Measuring Impact and Success in Data Engineering 23:06: Defining Professional Success 24:20: Building Leadership and Communication Skills 26:54: Future Aspirations and Career Goals Building in Public: The Best Way to Learn Data. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi—
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1: From Self-Driving Cars to Lead Data Engineer @ phData: Bruno Souza de Lima
03/10/2025
1: From Self-Driving Cars to Lead Data Engineer @ phData: Bruno Souza de Lima
Bolaji interviews Bruno Souza de Lima, an analytics engineer with a unique background in autonomous driving and programming. Bruno shares his journey from studying mechanical engineering to becoming a key contributor in the analytics community, emphasizing the importance of sharing knowledge, effective communication, and mentorship. He discusses his experiences with debugging data pipelines, the significance of community involvement, and his aspirations for future leadership roles. The conversation highlights the value of collaboration and continuous learning in the data field. As of the time of this recording, Bruno is the Lead Data Engineer at phData. Host: is the community manager at dbt Labs, and host of Data Career Transformations. Takeaways: Bruno's diverse background led him to analytics engineering. Understanding the difference between the internet and the web is crucial. Sharing knowledge can help others and build connections. You don't need to be an expert to contribute to the community. Effective communication with stakeholders is essential for success. Debugging involves breaking down complex problems into manageable parts. Having a mentor can significantly accelerate career growth. Introverts can create content without showing their face. Community involvement can lead to recognition and opportunities. Continuous learning and adaptation are key in the evolving data landscape. Timestamps: 00:00: Bruno's Journey into Autonomous Driving 04:25: Understanding the Web of Things 06:37: Transitioning to Analytics Engineering 08:31: Bruno's Career Development and Community Engagement 12:37: Communicating Technical Insights to Non-Technical Stakeholders 16:20: Overcoming Introversion in Content Creation 20:38: Debugging Strategies for Data Professionals 24:27: The Importance of Mentorship 32:53: Future Aspirations in Data Analytics Building in Public: The Best Way to Learn Data. We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. Crowdsource solutions—70,000+ people who’ve been there, done that. Find your crew—meet others who use the same tools you do. Stay at the cutting edge—discussions, meetups, and game shows keep things fresh. 👉 Jump in and say hi—
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