Databricks Data Engineer vs Data Analyst Associate: which should you take first?

The Databricks Certified Data Engineer Associate (DEA) and Data Analyst Associate (DAA) both sit at the associate level and share a real overlap: SQL, the medallion architecture (bronze/silver/gold) and core Lakehouse concepts. Past that overlap, they diverge fast — DEA is a pipelines-and-platform exam, DAA is a querying-and-dashboards exam.

The quick verdict

• Choose DAA if your work is closer to BI, reporting, or SQL-based analysis — you consume data more than you move it.
• Choose DEA if you build or maintain the pipelines that get data into the Lakehouse in the first place.
• Doing both? Either order works — the shared foundations mean the second exam always goes faster than the first.

Data Engineer Associate: pipelines and platform internals

DEA tests whether you can build, maintain and troubleshoot data pipelines the way Databricks expects them to be built — not generic data engineering, Databricks-flavoured data engineering.

• Format: ~45 questions, 90 minutes, pass at 70%.
• Core topics: Delta Lake internals (ACID, time travel, MERGE, OPTIMIZE, VACUUM), incremental ingestion with Auto Loader, the medallion architecture, and Unity Catalog governance.
• Feels like: "did you actually build a pipeline?" — scenario questions that punish textbook-only preparation.
• Best for: data engineers, ETL developers, and anyone responsible for getting data into the Lakehouse reliably.

Data Analyst Associate: SQL, dashboards and the Lakehouse for analytics

DAA assumes you're working with data that's already in the Lakehouse — querying it, visualising it, and applying basic analytics — rather than building the pipelines that put it there.

• Format: similar structure to DEA — around 45 questions, 90 minutes, pass at 70%.
• Core topics: SQL on Databricks, Databricks SQL warehouses, dashboards and visualisations, basic data modelling for analytics, and where governance (Unity Catalog) affects what an analyst can see.
• Feels like: a SQL-and-BI exam set inside the Databricks platform rather than a generic tool.
• Best for: data analysts, BI developers, and analytics engineers who query more than they pipeline.

If you want both, what order?

Coming from an analytics or BI background

Start with DAA — it matches your day-to-day SQL work and builds Lakehouse vocabulary you'll reuse directly when you move to DEA.

Coming from a data engineering or ETL background

Start with DEA — it's the heavier, more platform-specific exam, and DAA becomes a lighter add-on once you already know Unity Catalog and the medallion architecture.

How to prepare for either

Start free: try our sample questions for DEA and DAA. For both exams, the winning approach is the same: learn the concept, get hands-on with the platform, then drill realistic timed practice exams until you're consistently scoring above 80% — a solid safety margin over the 70% pass mark.