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.

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