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:

• 00:00: Introduction to Elize Papineau
• 02:59: Elize's Unique Background and Skills
• 05:54: Transition from Marine Biology to Data Engineering
• 09:02: Navigating the Data Job Market
• 12:00: Finding Identity in Data Roles
• 14:57: Continuous Learning and Skill Development
• 18:02: The Importance of Practical Experience
• 20:55: Discovering dbt and Its Impact
• 24:00: Working at Shopify and Personal Insights
• 24:07: Iced Tea: A Lifestyle Choice
• 25:10: Data Challenges at Shopify
• 27:01: Understanding Stakeholders and Their Needs
• 29:56: Data Disasters: Learning from Mistakes
• 34:38: Navigating Tough Interview Questions
• 39:24: Proud Projects and Their Impact
• 42:29: Measuring Business Impact
• 44:55: Influences and Mentorship in Data
• 47:38: Future Aspirations in the Data Community

Speakers:

• Guest: Elize Papineau is a Senior Data Engineer at Shopify.
• Host: Bolaji Oyejide 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

👉 Join the dbt Community

Subscribe on: Apple Podcasts | Spotify | YouTube | Amazon Music

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: 

• 00:00: Introduction to Tim Castillo and Chick-fil-A
• 03:04: The Role of Data in Location Strategy
• 06:59: Operational Efficiency and Intentionality at Chick-fil-A
• 09:02: Tim's Career Journey: From Software Engineer to Data Engineer
• 11:55: The Importance of Side Projects and Learning
• 15:00: The Evolution of Tim's Role in Data
• 18:02: Understanding Data Engineering vs. Data Science
• 20:57: Raising the Floor While Extending the Ceiling
• 25:03: Raising the Ceiling and Floor in Data Work
• 29:15: Team Structure and Scaling Challenges
• 30:59: The Role of dbt in Data Engineering
• 33:33: Learning from Data Disasters
• 36:49: 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

Join the dbt Community

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:

• 00:00: Introduction to Data Career Transformation
• 02:32: The Wandering Path to Analytics
• 06:32: The Great Filter in Data Careers
• 12:39: Non-Traditional Steps to Break Through
• 18:58: Taking a Chance on Analytics
• 20:56: Preparation Meets Opportunity
• 23:16: Navigating Career Paths in Data
• 27:57: The Evolution of Data Teams
• 30:41: Tech Stack Transformation at Smartsheet
• 32:58: Community and Networking in Data
• 36:48: Learning from Data Disasters
• 38:56: Building Trust Through Accountability
• 41:42: Lessons in Data Integrity
• 44:58: Proud Moments in Data Solutions
• 47:09: Measuring Impact in Data Teams
• 54:53: 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: Bolaji Oyejide 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

Join the dbt Community

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: Jessica Franks is the Data Engineering Manager at Not On the High Street, an eCommerce company based in the United Kingdom
• Host: Bolaji Oyejide 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:

• 00:00: Introduction to Jessica's Journey
• 02:33: From Telecom to Data Leadership
• 05:11: The Transition to Data Science
• 08:02: Navigating Career Changes
• 10:41: First Day at Not On The High Street
• 13:20: Building a Data Team
• 16:04: Creating a Data Strategy
• 18:40: The Importance of Communication in Data
• 21:20: Implementing Wardley Mapping
• 24:01: Modern Data Stack at Not On The High Street
• 25:49: The Value of dbt in Data Engineering
• 28:42: Change Management in Data Teams
• 32:00: Understanding Data Maturity
• 34:37: The Importance of Community and Mentorship
• 36:32: Asking Questions and Overcoming Hesitation
• 38:19: Handling Stress and Conflicting Priorities
• 40:58: Learning to Say No
• 42:51: Balancing Maintenance and Innovation
• 45:24: Measuring Impact in Data Roles
• 47:54: 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

Join the dbt Community

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: Ash Smith is the Manager of Data Platform at South32, a Mining company in Perth, Australia
• Host: Bolaji Oyejide 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:

• 00:00: Introduction to Ash Smith and His Journey
• 04:01: Ash's Current Role in Mining Data
• 07:27: Career Path and Transition to Data
• 10:29: Breaking into Online Gaming and Data Roles
• 12:33: Early Interests in Data and Patterns
• 16:08: Understanding Data Products
• 17:45: Evolving Data Practices and Challenges
• 19:30: Day-to-Day in Data Management
• 22:03: Navigating Data Disasters
• 23:45: Handling Stress and Burnout
• 26:58: The Challenge of Ad Hoc Requests
• 30:02: Celebrating Project Successes
• 33:30: Influences and Mentorship in Career
• 36:52: Building Relationships for Career Growth
• 39:41: Measuring Impact in Data Work
• 42:35: Technology's Role in Data Management
• 44:21: 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

Join the dbt Community

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: Kasey Mazza is the Director of Analytics Engineering at Hubspot
• Host: Bolaji Oyejide 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—Join the dbt Community now. 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:

• 00:00: Introduction to Kasey Mazza and Her Journey
• 02:54: Kasey's Data Origin Story
• 06:25: Applying the Software Development Life Cycle to Career Growth
• 09:41: The Role of an Analytics Engineering Manager
• 10:54: Building Data Teams Like a Community
• 12:36: Team Structure and Roles
• 14:59: Tech Stack and Tools Used
• 16:16: Data Challenges and Communication Gaps
• 19:29: Shaping Team Culture and Shared Language
• 20:19: Cultivating a Learning Culture
• 21:19: Investing in Personal Development
• 23:27: Beyond Titles: Collecting Skills
• 24:43: The Power of Reading
• 26:47: Building a Customer Score
• 29:43: Measuring Impact in Data
• 32:51: Defining Professional Success
• 34:08: The Influence of Mentorship
• 35:26: Looking Ahead: Future Aspirations
• 38:22: Advice for Aspiring Data Professionals

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: 

• 00:00: Introduction to Damola Onabanjo
• 02:20: The Journey to Business Intelligence
• 04:10: Understanding Kuda and Its Impact
• 05:26: Transitioning from Law to Data
• 07:12: Building a Career in Data Analytics
• 08:46: Navigating the Data Landscape
• 11:14: The Role of Personality in Data Careers
• 13:52: Exploring Data Roles and Responsibilities
• 15:55: Discovering dbt and Its Benefits
• 17:06: Discovering dbt and Building Skills
• 18:22: Navigating Data Disasters
• 21:40: Managing Stakeholder Expectations
• 23:49: The Art of Delegation
• 24:46: Fostering Team Collaboration
• 27:04: Building a Knowledge-Sharing Culture
• 29:36: Mentorship and Personal Growth
• 32:24: Advice for Aspiring Data Professionals

Speakers:

• Guest: Adedamola Onabanjo is the Business Intelligence Manager at Kuda
• Host: Bolaji Oyejide 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.

👉Join the dbt Community

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:

• 00:00:Introduction to Data Careers and Juggling
• 02:42: Wade's Journey into Data and Web Hosting
• 04:47: Transitioning to a Data-Driven Culture
• 06:57: The Evolution of Data in Web Hosting
• 09:11: Wade's Data Career and Love for SQL
• 11:47: Role of an Analytics Engineer
• 13:53: Day-to-Day Responsibilities of a Data Director
• 16:18: Team Structure and Data Engineering Challenges
• 18:33: Self-Service Data and Executive Needs
• 21:06: The Role of dbt in Data Transformation
• 22:19: The Evolution of Data Engineering
• 23:27: Navigating Data Disasters
• 27:06: The Importance of Domain Knowledge
• 28:53: Learning from Mistakes
• 31:17: Handling Stress and Expectations
• 35:33: Mentoring the Next Generation
• 40:23: 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

Join the dbt Community

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

Join the dbt Community

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

Join the dbt Community