Exam Name: Databricks Certified Data Engineer Professional
Certification Provider: Databricks
Corresponding Certification: Databricks Certification
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Databricks Certified-Data-Engineer-Professional Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Monitoring, Logging, and Troubleshooting | ~8% | - Use Spark UI, Query Profiler, and system tables - Diagnose common pipeline and job failures |
| Data Sharing and Federation | ~8% | - Configure Delta Sharing and Lakehouse Federation |
| Streaming Workloads and Change Data Capture | ~11% | - Implement reliable streaming pipelines - Apply AUTO CDC APIs and exactly-once semantics |
| Developing Code for Data Processing using Python and SQL | ~22% | - Build pipelines with Lakeflow Spark Declarative Pipelines and Auto Loader - Implement scalable Python/SQL code and project structures - Manage dependencies, libraries, and UDFs |
| Data Transformation, Cleansing, and Quality | ~12% | - Enforce data quality and quarantine bad data - Apply advanced Spark transformations |
| Cost and Performance Optimization | ~13% | - Optimize queries, clusters, and storage - Leverage system tables and observability tools |
| Data Modeling | ~10% | - Apply dimensional modeling techniques - Design scalable Delta Lake schemas and clustering |
| Security and Governance | ~10% | - Implement row-level security, column masking, and compliance - Manage Unity Catalog permissions and ACLs |
| CI/CD, Testing, and Deployment | ~6% | - Deploy with Declarative Automation Bundles, CLI, and REST API - Implement testing and deployment pipelines |
Databricks Certified Data Engineer Professional Sample Questions:
Review the following error traceback:
Which statement describes the error being raised?
- A. There is a type error because a column object cannot be multiplied.
- B. There is a type error because a DataFrame object cannot be multiplied.
- C. The code executed was PvSoark but was executed in a Scala notebook.
- D. There is a syntax error because the heartrate column is not correctly identified as a column.
- E. There is no column in the table named heartrateheartrateheartrate
Correct Answer: E 🗳️
Explanation: Only visible for ExamsLabs members. You can sign-up / login (it's free).
A security team wants to enforce data protection for a customer table containing customer PII data. To comply with local policies, sales team members should only see customers from their region, while non-admin users should have email addresses masked. Which implementation approach should be used when using Unity Catalog row filters and column masks?
- A. Use table ACLs to restrict access using tags with GRANT SELECT ON table_name WITH TAG command, and rely on application-level filtering for sensitive data based on user region.
- B. Create SQL UDFs for row filtering based on user region and column masking based on group membership, then apply them using ALTER TABLE SET ROW FILTER and ALTER COLUMN SET MASK commands.
- C. Implement row filters with SQL UDFs based on user region only since column masks cannot be combined with row filters on the same table, then apply them be recreating the table with DROP TABLE and CREATE TABLE SET ROW FILTER commands.
- D. Create a view with dynamic WHERE clauses for region filtering and use string replacement functions for email masking using ALTER COLUMN SET MASK command.
Correct Answer: B 🗳️
Explanation: Only visible for ExamsLabs members. You can sign-up / login (it's free).
A data engineer is using the AUTO CDC API in Lakeflow Spark Declarative Pipeline to propagate deletions from a source table (orders_source) to a target table (orders_target). The source has Change Data Feed (CDF) enabled, but some delete events arrive out of order due to upstream delays. How does the AUTO CDC API internally ensure deletions are applied correctly despite out-of-order events?
- A. It ignores deletions if they arrive after updates for the same key.
- B. It manually sorts incoming events by timestamp before applying changes.
- C. It runs VACUUM on the target table to purge conflicting records.
- D. It uses sequence_by to order events and retains tombstones for deleted rows until older sequences are processed.
Correct Answer: D 🗳️
Explanation: Only visible for ExamsLabs members. You can sign-up / login (it's free).
A member of the data engineering team has submitted a short notebook that they wish to schedule as part of a larger data pipeline. Assume that the commands provided below produce the logically correct results when run as presented.
Which command should be removed from the notebook before scheduling it as a job?
- A. Cmd 3
- B. Cmd 4
- C. Cmd 2
- D. Cmd 5
- E. Cmd 6
Correct Answer: E 🗳️
Explanation: Only visible for ExamsLabs members. You can sign-up / login (it's free).
A data engineer is implementing Unity Catalog governance for a multi-team environment. Data scientists need interactive clusters for basic data exploration tasks, while automated ETL jobs require dedicated processing. How should the data engineer configure cluster isolation policies to enforce least privilege and ensure Unity Catalog compliance?
- A. Create compute policies with STANDARD access mode for interactive workloads and DEDICATED access mode for automated jobs.
- B. Use only DEDICATED access mode for both interactive workloads and automated jobs to maximize security isolation.
- C. Allow all users to create any cluster type and rely on manual configuration to enable Unity Catalog access modes.
- D. Configure all clusters with NO ISOLATION_SHARED access mode since Unity Catalog works with any cluster configuration.
Correct Answer: A 🗳️
Explanation: Only visible for ExamsLabs members. You can sign-up / login (it's free).
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