Databricks-Certified-Data-Engineer-Professional Exam Dumps
Databricks Certified Data Engineer Professional Databricks-Certified-Data-Engineer-Professional real exam questions and online practice test engine by FreeCram. Try Databricks-Certified-Data-Engineer-Professional exam questions for free. You can also download a free demo of the Databricks-Certified-Data-Engineer-Professional exam PDF version.
Databricks's Databricks-Certified-Data-Engineer-Professional actual exam materials brought to you by FreeCram group of Databricks certification experts.
View all Databricks-Certified-Data-Engineer-Professional actual exam questions & answers and explanations for free.
If you like our product, you can request full access to all the latest Databricks Certified Data Engineer Professional Databricks-Certified-Data-Engineer-Professional exam premium questions.
| Certification Provider: | Databricks |
|---|---|
| Exam Code / Number: | Databricks-Certified-Data-Engineer-Professional |
| Exam Name: | Databricks Certified Data Engineer Professional Exam |
| Exam Questions: | 250 |
| Last Updated: | Oct 01, 2026 |
| Corresponding Certification: | Databricks Certification |
Go To Databricks-Certified-Data-Engineer-Professional Questions
(472 Up Votes)Databricks Databricks-Certified-Data-Engineer-Professional Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Monitoring and Alerting | 10% | - Monitor pipeline performance and health - Track data lineage and metrics - Set up alerts and notifications |
| Topic 2: Debugging and Deploying | 10% | - Troubleshoot and debug pipelines - Implement CI/CD and DevOps practices - Deploy using Asset Bundles, CLI, and APIs |
| Topic 3: Data Transformation, Cleansing, and Quality | 10% | - Implement schema evolution and management - Enforce data quality standards - Apply data cleansing and validation rules |
| Topic 4: Ensuring Data Security and Compliance | 10% | - Implement access control and permissions - Ensure data privacy and compliance - Secure data at rest and in transit |
| Topic 5: Cost & Performance Optimisation | 13% | - Improve query and pipeline performance - Optimize compute and storage resources - Apply cost management best practices |
| Topic 6: Data Governance | 7% | - Use Unity Catalog for governance - Enforce data policies and standards - Manage data assets and metadata |
| Topic 7: Developing Code for Data Processing using Python and SQL | 22% | - Use Databricks-specific libraries and APIs - Write efficient and maintainable code - Implement complex data processing logic |
| Topic 8: Data Modelling | 6% | - Optimize table design and partitioning - Implement dimensional and relational models - Design Medallion Architecture |
| Topic 9: Data Sharing and Federation | 5% | - Use Delta Sharing for secure data sharing - Manage cross-platform data access - Implement Lakehouse Federation |
| Topic 10: Data Ingestion & Acquisition | 7% | - Handle incremental and batch data loads - Use Auto Loader and structured streaming - Ingest data from diverse sources |