Data Engineer Professional resources

This exam assumes you have operated production pipelines. No resource list substitutes for that. If you have been on call for a job that degraded, debugged a skewed stage at an awkward hour and argued about cost attribution, the material is a refresher. If you have not, the honest advice is to get six to twelve months of that experience first.

Start with the official material

The exam guide and its weights: developing code for data processing 22%, cost and performance optimisation 13%, then transformation and quality, monitoring and alerting, security and compliance, and debugging and deploying at 10% each, with ingestion and governance at 7% each.

Databricks Academy’s advanced material. Written to this level rather than the associate one.

The performance and optimisation documentation. This exam asks about specific mechanisms — file skipping, clustering, adaptive execution, shuffle behaviour — with more precision than summaries carry.

What to practise

Everything here assumes an associate-level foundation already.

• Exactly-once semantics: checkpointed offsets plus an idempotent or transactional sink. Kill the job mid-write and confirm the result.
• Replace a row-at-a-time Python UDF with built-in expressions on a large dataset, and measure the difference. The serialisation cost becomes visceral.
• Force a broadcast join and then prevent one, and read the plan in each case.
• Create deliberate skew, watch a handful of tasks dominate the stage, then mitigate it.
• Build one transformation that runs identically for backfill and incremental, parameterised only by read and write mode.
• Extract logic into a versioned module with unit tests, so it is testable outside a notebook.
• Work through an erasure request against a table with retained history, and think about versions, downstream copies and vacuum policy.

That last one is the security and compliance question people get wrong: deleting the current row is not sufficient.

The passing score problem

Databricks publishes no passing score. At professional level this matters more, because the margin is narrower and you have no official target. A weighted practice test is the only calibration available — the free 20-question test here matches the published sections.

Worth paying for

A practice test with explanations, for calibration.

Employer-funded advanced training, which is worth more at this level than at associate, because the material is harder to self-structure.

Compute for realistic data volumes. Skew and small-file problems do not reproduce on toy datasets, and these are exam topics.

What to skip

Braindumps.

Associate-level material. If you still need it, you are not ready for this exam and should sit the associate first.

Anything promising a fast pass. This is not an exam that rewards cramming.

A sensible order

1. Read the exam guide. Note that code development is the largest block at 22%.
2. Work through the advanced Academy material.
3. Practise the seven items above at realistic data volumes.
4. Take the practice test.
5. Return to documentation, not summaries, for the weakest section.

Are you ready for this one?

The Databricks certification path is blunt about the gap between associate and professional. If the associate exam was hard, this one is not the next step yet.