Description
The Databricks Certified Data Engineer Professional exam evaluates a candidate’s ability to use the Databricks Data Intelligence Platform to perform advanced data engineering tasks. This includes building, optimizing, and maintaining production-grade ETL pipelines, processing complex data from diverse sources using Python and SQL, and leveraging core platform features such as Delta Lake, Unity Catalog, Auto Loader, Lakeflow Spark Declarative Pipelines, Databricks Compute (including serverless), Lakeflow Jobs, and the Medallion Architecture. The exam assesses skills in implementing streaming workloads, orchestrating workflows, applying DevOps and CI/CD practices, and deploying solutions using tools like the Databricks CLI, REST API, and Asset Bundles. Candidates are also tested on applying best practices in schema management, observability, data governance, performance optimization, and security to ensure reliable, secure, and cost-effective data engineering solutions.
This exam covers:
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Developing Code for Data Processing using Python and SQL – 22%
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Data Ingestion & Acquisition – 7%
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Data Transformation, Cleansing, and Quality – 10%
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Data Sharing and Federation – 5%
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Monitoring and Alerting – 10%
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Cost & Performance Optimization – 13%
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Ensuring Data Security and Compliance – 10%
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Data Governance – 7%
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Debugging and Deploying – 10%
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Data Modelling – 6%
