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Updated: Aug 26, 2026
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| Certification Vendor: | Databricks |
| Exam Name: | Databricks Certified Data Engineer Professional |
| Exam Number: | Certified-Data-Engineer-Professional |
| Exam Price: | USD 200 plus applicable taxes |
| Real Exam Qty: | 59 scored multiple-choice questions |
| Exam Format: | Multiple-choice questions, Online proctored, Test center proctored |
| Related Certifications: | Databricks Certified Data Engineer Associate |
| Available Languages: | English |
| Certificate Validity Period: | 2 years |
| Exam Duration: | 120 minutes |
| Recommended Training: | Databricks Academy Advanced Data Engineering with Databricks |
| Exam Registration: | Databricks Certified Data Engineer Professional Certification |
| Sample Questions: | Databricks Certified-Data-Engineer-Professional Sample Questions |
| Exam Way: | Online proctored or test center proctored |
| Pre Condition: | No prerequisite is required. Related course attendance and one year of hands-on experience in data engineering tasks covered by the exam are highly recommended. |
| Official Syllabus URL: | https://www.databricks.com/sites/default/files/2025-11/databricks-certified-data-engineer-professional-exam-guide-november-30-2025.pdf |
| Section | Objectives |
|---|---|
| Data Ingestion & Acquisition | - Design and implement data ingestion pipelines
|
| Data Modeling | - Design and optimize data models
|
| Debugging and Deploying | - Deploying CI/CD
|
| Monitoring and Alerting | - Alerting
|
| Ensuring Data Security and Compliance | - Applying Data Security Mechanisms
|
| Data Governance | - Govern enterprise data
|
| Cost & Performance Optimization | - Optimize cost and performance
|
| Data Sharing and Federation | - Share and federate data
|
| Developing Code for Data Processing using Python and SQL | - Using Python and Tools for Development
|
| Data Transformation, Cleansing, and Quality | - Transform and validate data
|
1. An analytics team wants to run a short-term experiment in Databricks SQL on the customer transactions Delta table (about 20 billion records) created by the data engineering team. Which strategy should the data engineering team use to ensure minimal downtime and no impact on the ongoing ETL processes?
A) Deep clone the table for the analytics team.
B) Shallow clone the table for the analytics team.
C) Give the analytics team direct access to the production table.
D) Create a new table for the analytics team using a CTAS statement.
2. A production cluster has 3 executor nodes and uses the same virtual machine type for the driver and executor.
When evaluating the Ganglia Metrics for this cluster, which indicator would signal a bottleneck caused by code executing on the driver?
A) The five Minute Load Average remains consistent/flat
B) Bytes Received never exceeds 80 million bytes per second
C) Overall cluster CPU utilization is around 25%
D) Network I/O never spikes
E) Total Disk Space remains constant
3. A Delta table of weather records is partitioned by date and has the below schema:
date DATE, device_id INT, temp FLOAT, latitude FLOAT, longitude FLOAT
To find all the records from within the Arctic Circle, you execute a query with the below filter:
latitude > 66.3
Which statement describes how the Delta engine identifies which files to load?
A) The Delta log is scanned for min and max statistics for the latitude column
B) All records are cached to attached storage and then the filter is applied
C) The Hive metastore is scanned for min and max statistics for the latitude column
D) The Parquet file footers are scanned for min and max statistics for the latitude column
E) All records are cached to an operational database and then the filter is applied
4. A view is registered with the following code:
Both users and orders are Delta Lake tables.
Which statement describes the results of querying recent_orders?
A) All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query began.
B) The versions of each source table will be stored in the table transaction log; query results will be saved to DBFS with each query.
C) All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query finishes.
D) All logic will execute when the table is defined and store the result of joining tables to the DBFS; this stored data will be returned when the table is queried.
5. A data engineer wants to enforce the principle of least privilege when configuring ACLs for Databricks jobs in a collaborative workspace. Which approach should the data engineer use?
A) Assign users only the minimum permission level (e.g., CAN RUN or CAN VIEW) required for their role on each job.
B) Grant all users CAN MANAGE permission on all jobs to avoid access issues.
C) Grant CAN RUN permission to everyone and CAN MANAGE to a single admin group.
D) Use only folder-level permissions and avoid setting permissions on individual jobs.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: C | Question # 3 Answer: A | Question # 4 Answer: A | Question # 5 Answer: A |
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