Databricks Databricks-Certified-Data-Engineer-Professional : Databricks Certified Data Engineer Professional Exam

  • Exam Code: Databricks-Certified-Data-Engineer-Professional
  • Exam Name: Databricks Certified Data Engineer Professional Exam
  • Updated: Oct 12, 2026     Q & A: 250 Questions and Answers

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Following are some reference material for actual Databricks Databricks-Certified-Data-Engineer-Professional exam test

Databricks Databricks-Certified-Data-Engineer-Professional Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Monitoring and Troubleshooting16%- Performance Optimization
- Troubleshooting
- Monitoring
Topic 2: Data Quality and Governance12%- Data Quality
- Data Lineage
- Governance
Topic 3: Data Modeling and Storage20%- Storage Optimization
- File Formats
- Data Modeling
Topic 4: Databricks Lakehouse Platform24%- Data Management
- Lakehouse Architecture
- Delta Lake
- Unity Catalog
Topic 5: Data Processing28%- Structured Streaming
- Data Transformation
- ETL Pipelines
- Spark SQL

Databricks Certified Data Engineer Professional Sample Questions:

Question #1

The DevOps team has configured a production workload as a collection of notebooks scheduled to run daily using the Jobs Ul. A new data engineering hire is onboarding to the team and has requested access to one of these notebooks to review the production logic. What are the maximum notebook permissions that can be granted to the user without allowing accidental changes to production code or data?

  • A. Can edit
  • B. Can Read
  • C. Can manage
  • D. Can run
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #2

A data engineer is brining an existing production Databricks job under asset bundle management and wants to ensure that:
- The job's current configuration is captured as YAML, and all
referenced files are included in their bundle project.
- Future changes to the bundle's YAML will update the existing job in-
place (not create a new job)
How should the data engineer successfully move the production job under asset bundle management?

  • A. Run databricks bundle generate job --existing-job-id to generate the YAML and download referenced files. Then, run Databricks bundle deployment, bind to link the bundle's job resource to the existing job in Databricks.
  • B. Manually create the YAML configuration for the job in your bundle project, ensuring all settings match the existing job. Then, run Databricks bundle deploy the bundle, which will update the existing job in your workspace.
  • C. Run Databricks bundle generate job --existing-job-id to generate the YAML and download referenced files. Then, run Databricks bundle deploy to deploy the bundle, which will always update the existing job automatically.
  • D. Export the job definition as JSON, convert it to YAML, and place it in your bundle. Then, run Databricks bundle deploy to update the existing job.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Question #3

An external object storage container has been mounted to the location /mnt/finance_eda_bucket.
The following logic was executed to create a database for the finance team:

After the database was successfully created and permissions configured, a member of the finance team runs the following code:

If all users on the finance team are members of the finance group, which statement describes how the tx_sales table will be created?

  • A. An managed table will be created in the storage container mounted to /mnt/finance_eda_bucket.
  • B. A managed table will be created in the DBFS root storage container.
  • C. A logical table will persist the query plan to the Hive Metastore in the Databricks control plane.
  • D. An external table will be created in the storage container mounted to /mnt/finance eda bucket.
  • E. A logical table will persist the physical plan to the Hive Metastore in the Databricks control plane.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Question #4

A data engineer us ingesting JSON files from cloud object storage using Databricks Auto Loader.
The source folder may occasionally receive large files of data, which risks overwhelming the stream. To ensure predictable micro-batch sizes, the team wants to throttle ingestion based on the volume of data scanned at 1 GB, regardless of the number of files. Which Auto Loader configuration should the data engineer used to achieve this?

  • A. Configure cloudFiles.maxSizePerTrigger with 1 GB to place a limit.
  • B. Configure cloudFiles.maxPartitionBytes with 1GB to limit data in each partition.
  • C. Configure cloudFiles.maxFilesPerTrigger and estimate the average file size to approximate a size-based throttle of 1 GB.
  • D. Configure cloudFiles.maxBytesPerTrigger with 1 GB to place a limit.
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #5

The data architect has mandated that all tables in the Lakehouse should be configured as external (also known as "unmanaged") Delta Lake tables.
Which approach will ensure that this requirement is met?

  • A. When a database is being created, make sure that the LOCATION keyword is used.
  • B. When configuring an external data warehouse for all table storage, leverage Databricks for all ELT.
  • C. When tables are created, make sure that the EXTERNAL keyword is used in the CREATE TABLE statement.
  • D. When data is saved to a table, make sure that a full file path is specified alongside the Delta format.
  • E. When the workspace is being configured, make sure that external cloud object storage has been mounted.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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