- Exam Code: Databricks-Certified-Professional-Data-Engineer
- Exam Name: Databricks Certified Professional Data Engineer Exam
- Updated: Oct 13, 2026
- Q & A: 217 Questions and Answers
Databricks Certified Professional Data Engineer : Databricks-Certified-Professional-Data-Engineer
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Databricks Databricks-Certified-Professional-Data-Engineer Exam Syllabus Topics:
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Reference: https://www.databricks.com/learn/certification/data-engineer-professional
Databricks Certified Professional Data Engineer Sample Questions:
Question #1
Which statement regarding stream-static joins and static Delta tables is correct?
- A. The checkpoint directory will be used to track updates to the static Delta table.
- B. Stream-static joins cannot use static Delta tables because of consistency issues.
- C. The checkpoint directory will be used to track state information for the unique keys present in the join.
- D. Each microbatch of a stream-static join will use the most recent version of the static Delta table as of the job ' s initialization.
- E. Each microbatch of a stream-static join will use the most recent version of the static Delta table as of each microbatch.
Correct Answer: E 🗳️
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Question #2
A Databricks SQL dashboard has been configured to monitor the total number of records present in a collection of Delta Lake tables using the following query pattern:
SELECT COUNT (*) FROM table -
Which of the following describes how results are generated each time the dashboard is updated?
- A. The total count of records is calculated from the parquet file metadata
- B. The total count of records is calculated from the Delta transaction logs
- C. The total count of rows is calculated by scanning all data files
- D. The total count of records is calculated from the Hive metastore
- E. The total count of rows will be returned from cached results unless REFRESH is run
Correct Answer: B 🗳️
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Question #3
A distributed team of data analysts share computing resources on an interactive cluster with autoscaling configured. In order to better manage costs and query throughput, the workspace administrator is hoping to evaluate whether cluster upscaling is caused by many concurrent users or resource-intensive queries.
In which location can one review the timeline for cluster resizing events?
- A. Cluster Event Log
- B. Executor ' s log file
- C. Driver ' s log file
- D. Workspace audit logs
- E. Ganglia
Correct Answer: A 🗳️
Question #4
A junior data engineer has manually configured a series of jobs using the Databricks Jobs UI. Upon reviewing their work, the engineer realizes that they are listed as the " Owner " for each job. They attempt to transfer " Owner " privileges to the " DevOps " group, but cannot successfully accomplish this task.
Which statement explains what is preventing this privilege transfer?
- A. The creator of a Databricks job will always have " Owner " privileges; this configuration cannot be changed.
- B. Only workspace administrators can grant " Owner " privileges to a group.
- C. Databricks jobs must have exactly one owner; " Owner " privileges cannot be assigned to a group.
- D. A user can only transfer job ownership to a group if they are also a member of that group.
- E. Other than the default " admins " group, only individual users can be granted privileges on jobs.
Correct Answer: C 🗳️
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Question #5
A data engineer is tasked with ensuring that a Delta table in Databricks continuously retains deleted files for
15 days instead of the default 7 days, in order to comply with the organization's data retention policy. Which code snippet correctly sets this retention period for deleted files?
- A. spark.sql( " VACUUM my_table RETAIN 15 HOURS " )
- B. from delta.tables import *
deltaTable = DeltaTable.forPath(spark, " /mnt/data/my_table " )
deltaTable.deletedFileRetentionDuration = " interval 15 days " - C. spark.conf.set( " spark.databricks.delta.deletedFileRetentionDuration " , " 15 days " )
- D. spark.sql( " " "
ALTER TABLE my_table
SET TBLPROPERTIES ( ' delta.deletedFileRetentionDuration ' = ' interval 15 days ' )
" " " )
Correct Answer: D 🗳️
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