The Rise of the Analytics Engineer: A New Role in Modern Data Teams

There’s a new role emerging between data engineering and data analysis: the analytics engineer. Understanding this role is key to building an effective modern data team.

What Analytics Engineers Do

Analytics engineers own the transformation layer. They take raw data that data engineers have loaded into the warehouse and model it into clean, well-documented datasets that analysts and business users can query directly. Their primary tool is dbt.

How It Differs From Traditional Roles

Data engineers focus on infrastructure — pipelines, orchestration, and reliability. Data analysts focus on insights — dashboards, reports, and ad-hoc analysis. Analytics engineers bridge the gap by ensuring the data between these layers is modeled correctly and thoroughly tested.

Why This Role Matters

Before analytics engineers, there was a persistent gap. Data engineers would load raw data into the warehouse, but analysts couldn’t use it without extensive SQL gymnastics. Analytics engineers fill this gap with modular, version-controlled transformations that make data accessible to everyone.

If your data team is growing, consider adding analytics engineering as a distinct function. It dramatically improves data quality and reduces the burden on both engineers and analysts.