Data Career Transformations

dbt Labs

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 podcast@dbtlabs.com

  1. 2 SEPT

    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: 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—join the dbt Community now.

    44 min

  2. 31 AUG

    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: Millie Symns, Senior BI Analyst at JustWorks 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—join the dbt Community now.

    46 min

  3. 29 AUG

    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: Johnathan JB Brooks, former Director of Data Engineering at BetterHelp. (Now Principal Data & AI Architect at Astrodata) 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—join the dbt Community now.

    55 min

  4. 28 AUG

    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: Eddy Zulkifly, Senior Staff Data Engineer, Kinaxis 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—join the dbt Community now.

    45 min

  5. 26 AUG

    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: Apple Podcasts | Spotify | YouTube | Amazon Music   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: Louis Guitton, AI Solutions Architect and ML Engineer 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—join the dbt Community now.

    42 min

  6. 1 AUG

    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: Larissa Mendes, Data Engineer II at Gupy 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—join the dbt Community now.

    44 min

  7. 28 JUL

    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:  Apple Podcasts | Spotify | YouTube | Amazon Music   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:  00:00 Introduction to Yannick's Journey 02:00 The Unexpected Path to Dance 04:53 From Quantum Physics to Data Science 10:25 Transitioning from Academia to Industry 13:47 Consulting Experience and Its Impact 15:32 Personality and Career Fit in Data Roles 18:16 The Triad of People, Process, and Technology 18:57 People, Process, and Technology: The Triad of Success 20:39 Climbing the Corporate Ladder: Yannick's Journey 22:44 The Role of dbt in Data Transformation 24:27 Learning from Data Disasters: The Importance of Testing 26:17 Communicating Business Value: The Data Leader's Challenge 28:29 Managing Stress: Balancing Work and Life 30:30 Mentorship and Inspiration: Learning from Others 32:21 Advice for Aspiring Data Professionals: Building a Foundation   Speakers:  Guest: Yannick Misteli, Head of Engineering, Global Pharma Strategy, Roche Host: Bolaji Oyejide, 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—join the dbt Community now.

    36 min

  8. 10 JUL

    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: Apple Podcasts | Spotify | YouTube | Amazon Music   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: Philip Boontje, MaxQ Analytics Data Engineer & Guild Lead 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—join the dbt Community now.

    44 min
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About

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 podcast@dbtlabs.com

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