This is what I’m reading this week.

• https://medium.com/@mikldd/how-top-data-teams-are-structured-48d46a64b990

  • An interesting article that explores the mix of roles for data teams across industries. The author, Mikkel Dengsøe outlines the following roles:

    Insight — Data Analysts, Product Analysts, Data Scientists

    Data Engineering — Data Engineers, Data Platform Engineers, Analytics Engineers, Data Governance

    Machine Learning — Machine Learning Engineers

    • My takeawys were the following:
      • The median composition of data teams across 40 top companies shows a slight preference for insights roles over data engineering roles. Specifically, 46% of team members are in insights roles (such as data analysts and data scientists), while 43% are in data engineering roles (including data engineers and analytics engineers)
      • Data team composition varies significantly based on company size and maturity. Mid-size companies (with data teams smaller than 35 people) tend to have a higher proportion of data engineering roles. In contrast, larger scale companies (with data teams of 100+ people) have a significantly higher share of machine learning roles and are more likely to have dedicated data governance functions.