Free Certification Practice Questions

Validates proficiency with the Databricks Data Intelligence Platform for introductory data engineering tasks, including understanding the platform architecture and multi-cloud workspace, performing ETL using Apache Spark SQL and PySpark, handling complex data transformations and user-defined functions, deploying and orchestrating workloads with Databricks Workflows, and applying data governance and quality practices with Unity Catalog.

Validates advanced skills in building, optimising, and maintaining production-grade data engineering solutions on the Databricks Data Intelligence Platform. Covers Delta Lake, Unity Catalog, Auto Loader, Lakeflow Spark Declarative Pipelines, Databricks Compute (including serverless), Lakeflow Jobs, and the Medallion Architecture. Assesses the ability to design secure, reliable, and cost-effective ETL pipelines, process complex data using Python and SQL, and apply best practices in schema management, observability, governance, and performance optimization. Also covers streaming workloads, workflow orchestration, DevOps and CI/CD, and deploying with the Databricks CLI, REST API, and Asset Bundles.