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Exam Code: Databricks-Certified-Data-Engineer-Professional
Exam Name: Databricks Certified Data Engineer Professional Exam
Updated: Oct 26, 2026
Q & A: 250 Questions and Answers
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Databricks Databricks-Certified-Data-Engineer-Professional Exam Syllabus Topics:

Section	Weight	Objectives
Data Transformation, Cleansing, and Quality	10%	- Apply data cleansing and validation rules - Implement schema evolution and management - Enforce data quality standards
Data Sharing and Federation	5%	- Use Delta Sharing for secure data sharing - Implement Lakehouse Federation - Manage cross-platform data access
Cost & Performance Optimisation	13%	- Optimize compute and storage resources - Improve query and pipeline performance - Apply cost management best practices
Monitoring and Alerting	10%	- Set up alerts and notifications - Track data lineage and metrics - Monitor pipeline performance and health
Developing Code for Data Processing using Python and SQL	22%	- Write efficient and maintainable code - Implement complex data processing logic - Use Databricks-specific libraries and APIs
Debugging and Deploying	10%	- Implement CI/CD and DevOps practices - Troubleshoot and debug pipelines - Deploy using Asset Bundles, CLI, and APIs
Data Ingestion & Acquisition	7%	- Use Auto Loader and structured streaming - Ingest data from diverse sources - Handle incremental and batch data loads
Data Governance	7%	- Use Unity Catalog for governance - Enforce data policies and standards - Manage data assets and metadata
Ensuring Data Security and Compliance	10%	- Ensure data privacy and compliance - Implement access control and permissions - Secure data at rest and in transit
Data Modelling	6%	- Optimize table design and partitioning - Implement dimensional and relational models - Design Medallion Architecture

Databricks Certified Data Engineer Professional Sample Questions:

Question #1

All records from an Apache Kafka producer are being ingested into a single Delta Lake table with the following schema:
key BINARY, value BINARY, topic STRING, partition LONG, offset LONG, timestamp LONG There are 5 unique topics being ingested. Only the "registration" topic contains Personal Identifiable Information (PII). The company wishes to restrict access to PII. The company also wishes to only retain records containing PII in this table for 14 days after initial ingestion.
However, for non-PII information, it would like to retain these records indefinitely.
Which of the following solutions meets the requirements?

A. Data should be partitioned by the topic field, allowing ACLs and delete statements to leverage partition boundaries.
B. Separate object storage containers should be specified based on the partition field, allowing isolation at the storage level.
C. All data should be deleted biweekly; Delta Lake's time travel functionality should be leveraged to maintain a history of non-PII information.
D. Data should be partitioned by the registration field, allowing ACLs and delete statements to be set for the PII directory.
E. Because the value field is stored as binary data, this information is not considered PII and no special precautions should be taken.

Reveal Solution Discussion 0

Correct Answer: A 🗳️