Most data teams have similar players and types of work.

This includes not just people on the core data engineering side, but others that operate around it.

While the specific naming and responsibilities will vary by company, this video will break down some of the most common structures I've seen in my career.

By the end, you'll walk away with a better understanding of common overall layouts to expect, or if you're trying to start your own team, how you can think about getting organized.

Thank you for watching!

The Starter Guide to the Modern Data Stack - https://bit.ly/3MdORqn

▬▬▬▬▬▬ T I M E S T A M P S ⏰ ▬▬▬▬▬▬
0:00 - Intro
0:15 - High-level overview
0:45 - Product
1:30 - Data Engineer
1:59 - Data Analyst
2:46 - Analytics Engineer
4:15 - Data Scientist

Common Data Team Structures (Engineer vs Analyst vs Scientist)
#kahandatasolutions #dataengineering #dataanalytics