Databricks

30 Minutes

15 Questions

This assessment evaluates the skills of senior data engineers in working with Databricks at scale. It focuses on Databricks architecture, Delta Lake internals, cluster design, Spark performance tuning, metadata and file management, and enterprise data pipeline optimization. The goal is to demonstrate deep hands-on experience building and optimizing large-scale data solutions in Databricks within a modern cloud environment.

Example Question:

Multiple-Choice

You partition a table by event_date and perform frequent DELETEs on small date ranges. Performance regresses after the upgrade. Why?

Answers

1. Delta 3.2 forces full table scans when filters include deleted values

2. DELETEs generate many small checkpoints, increasing storage metadata pressure.

3. Photon converts DELETEs to MERGE statements

4. Unity Catalog enforces row-level locks