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Updated: Aug 30, 2026

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Databricks Databricks-Certified-Professional-Data-Engineer Exam Overview:

Certification Vendor:Databricks
Exam Name:Databricks Certified Professional Data Engineer Exam
Exam Number:Databricks-Certified-Professional-Data-Engineer
Passing Score:70%
Available Languages:English
Exam Format:Multiple choice, Scenario-based questions, Multiple select
Exam Price:USD 200
Related Certifications:Databricks Certified Data Engineer Associate
Real Exam Qty:60-70
Certificate Validity Period:2 years
Exam Duration:120 minutes
Recommended Training:Databricks Academy
Exam Registration:Databricks Certification Portal
Sample Questions:Databricks Databricks-Certified-Professional-Data-Engineer Sample Questions
Exam Way:Online proctored exam
Pre Condition:Recommended: Databricks Certified Data Engineer Associate or equivalent experience with Spark and Databricks platform.
Official Syllabus URL:https://www.databricks.com/learn/certification

Databricks Databricks-Certified-Professional-Data-Engineer Exam Syllabus Topics:

TopicDetails
Topic 1
  • Testing & Deployment: It discusses adapting notebook dependencies to use Python file dependencies, leveraging Wheels for imports, repairing and rerunning failed jobs, creating jobs based on common use cases, designing systems to control cost and latency SLAs, configuring the Databricks CLI, and using the REST API to clone a job, trigger a run, and export the run output.
Topic 2
  • Data Modeling: It focuses on understanding the objectives of data transformations, using Change Data Feed, applying Delta Lake cloning, designing multiplex bronze tables. Lastly it discusses implementing incremental processing and data quality enforcement, implementing lookup tables, and implementing Slowly Changing Dimension tables, and implementing SCD Type 0, 1, and 2 tables.
Topic 3
  • Monitoring & Logging: This topic includes understanding the Spark UI, inspecting event timelines and metrics, drawing conclusions from various UIs, designing systems to control cost and latency SLAs for production streaming jobs, and deploying and monitoring both streaming and batch jobs.
Topic 4
  • Databricks Tooling: The Databricks Tooling topic encompasses the various features and functionalities of Delta Lake. This includes understanding the transaction log, Optimistic Concurrency Control, Delta clone, indexing optimizations, and strategies for partitioning data for optimal performance in the Databricks SQL service.
Topic 5
  • Data Processing: The topic covers understanding partition hints, partitioning data effectively, controlling part-file sizes, updating records, leveraging Structured Streaming and Delta Lake, implementing stream-static joins and deduplication. Additionally, it delves into utilizing Change Data Capture and addressing performance issues related to small files.

Reference: https://www.databricks.com/learn/certification/data-engineer-professional

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