A failed Certified-Data-Engineer-Professional attempt costs the full exam fee plus weeks of morale. The Databricks Certified Data Engineer Professional practice questions from ValidDumps, 250 items refined by daily expert review, exist to make that an expense you never meet.
| Certification Vendor: | Databricks |
|---|---|
| Exam Name: | Databricks Certified Data Engineer Professional |
| Exam Number: | Certified-Data-Engineer-Professional |
| Exam Format: | Online proctored, Multiple-choice questions, Test center proctored |
| Real Exam Qty: | 59 scored multiple-choice questions |
| Available Languages: | English |
| Exam Price: | USD 200 plus applicable taxes |
| Related Certifications: | Databricks Certified Data Engineer Associate |
| Exam Duration: | 120 minutes |
| Certificate Validity Period: | 2 years |
| Recommended Training: | Advanced Data Engineering with Databricks Databricks Academy |
| Exam Registration: | Databricks Certified Data Engineer Professional Certification |
| 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 |
|---|---|
| Topic 1: Data Modeling | - Design and optimize data models
|
| Topic 2: Data Ingestion & Acquisition | - Design and implement data ingestion pipelines
|
| Topic 3: Debugging and Deploying | - Debugging and Troubleshooting
|
| Topic 4: Data Sharing and Federation | - Share and federate data
|
| Topic 5: Data Governance | - Govern enterprise data
|
| Topic 6: Monitoring and Alerting | - Alerting
|
| Topic 7: Cost & Performance Optimization | - Optimize cost and performance
|
| Topic 8: Developing Code for Data Processing using Python and SQL | - Building and Testing an ETL Pipeline with Lakeflow Declarative Pipelines, SQL, and Apache Spark
|
| Topic 9: Data Transformation, Cleansing, and Quality | - Transform and validate data
|
| Topic 10: Ensuring Data Security and Compliance | - Ensuring Compliance
|
Databricks Certified Data Engineer Professional is an official Databricks certification exam, listed under the code Certified-Data-Engineer-Professional. Clearing it earns the Databricks Certified Data Engineer Professional certification, a Professional-level credential. It also ties into Databricks Certified Data Engineer Associate, which makes it a useful anchor for a longer certification plan. For employers, the value is simple: the vendor itself has verified what you know.
You will work through 59 scored multiple-choice questions questions in 120 minutes on the Databricks Certified Data Engineer Professional exam. The content is only half the battle; the clock is the other half. Train both at once: set the ValidDumps test engine to full timed mode, practice skipping and returning to stubborn items, and repeat until finishing with minutes to spare feels normal rather than lucky.
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.
Requirements do evolve, so before you spend a registration fee, verify the current conditions on the official exam page.
Registration for Databricks Certified Data Engineer Professional is handled through the vendor's official channels below.
One more detail for your planning: the exam is delivered Online proctored or test center proctored.
Databricks recommends the following training resources for the Databricks Certified Data Engineer Professional exam.
Training tells you what to learn; practice questions teach you how the exam asks it. Pair either with the 250 items in the ValidDumps Certified-Data-Engineer-Professional package and you cover both halves.
Yes. The free demo on this page contains a portion of the complete Databricks Certified Data Engineer Professional question set, enough to judge the accuracy and the clarity of the explanations for yourself. After purchase, updates are free for 365 days, and once your product expires you can extend the update service at a 50% discount.
ValidDumps provides a 100% money-back guarantee with clearly stated conditions. Take the Databricks Certified Data Engineer Professional exam within 60 days of purchase; if you fail, you may claim a full refund, as long as the exam matches your product. Exams taken within 3 days of purchase are not eligible, and neither are products that were downloaded but never used, free materials, or expired orders; the candidate name must match the payer name. File the claim with a scanned enrollment slip and the official Score Report PDF within 2 days of the exam, and it is processed within 7 days. If you would rather exchange than refund, you can receive two other exam products of equal value free of charge and keep the update service on your original purchase.
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The official Databricks Certified Data Engineer Professional syllabus comprises 10 domains. The heaviest hitters are Developing Code for Data Processing using Python and SQL, Cost & Performance Optimization, and Ensuring Data Security and Compliance. The complete outline sits above on this page; walk it top to bottom and mark every line you could not teach to someone else.
Question 1
The following table consists of items found in user carts within an e-commerce website.
The following MERGE statement is used to update this table using an updates view, with schema evolution enabled on this table.
How would the following update be handled?
A. The update is moved to separate ''restored'' column because it is missing a column expected in the target schema.
B. The new nested field is added to the target schema, and files underlying existing records are updated to include NULL values for the new field.
C. The update throws an error because changes to existing columns in the target schema are not supported.
D. The new restored field is added to the target schema, and dynamically read as NULL for existing unmatched records.
Question 2
A data engineering workspace was automatically enabled for Unity Catalog, creating a workspace catalog. New team members report they can create tables in the default schema but cannot access table in other schemas within the same workspace catalog. Why are the new team members unable to access tables in other schemas?
A. Tables in other schemas require additional BROWSEprivileges that new users don't receive automatically
B. New users only receive CREATE TABLE privileges on the default schema.
C. Workspace catalog permissions are not subject to inheritance rules.
D. Workspace users receive USE CATALOG and specific privileges on default schema only.
Question 3
A data engineer wants to refactor the following DLT code, which includes multiple table definitions with very similar code.
In an attempt to programmatically create these tables using a parameterized table definition, the data engineer writes the following code.
The pipeline runs an update with this refactored code, but generates a different DAG showing incorrect configuration values for these tables.
How can the data engineer fix this?
A. Wrap the loop inside another table definition, using generalized names and properties to replace with those from the inner table
B. Load the configuration values for these tables from a separate file, located at a path provided by a pipeline parameter.
C. Convert the list of configuration values to a dictionary of table settings, using table names as keys.
D. Convert the list of configuration values to a dictionary of table settings, using different input the for loop.
Question 4
A data engineer is working in an interactive notebook with many transformations before outputting the result from display(df.collect() ). The notebook includes wide transformations and a cross join.
The data engineer is getting the following error: "The spark driver has stopped unexpectedly and is restarting. Your notebook will be automatically reattached." Which action should the data engineer take?
A. Run the notebook on a single node cluster to keep driver from falling.
B. Check into the Spark UI to see how many jobs are assigned to each stage as they are employing fewer executors.
C. Look at the compute metrics UI to see if the executors have higher than 90% memory utilization.
D. Rewrite their code to avoid putting memory pressure on the driver node.
Question 5
The data engineer team has been tasked with configured connections to an external database that does not have a supported native connector with Databricks. The external database already has data security configured by group membership. These groups map directly to user group already created in Databricks that represent various teams within the company. A new login credential has been created for each group in the external database. The Databricks Utilities Secrets module will be used to make these credentials available to Databricks users. Assuming that all the credentials are configured correctly on the external database and group membership is properly configured on Databricks, which statement describes how teams can be granted the minimum necessary access to using these credentials?
A. "Manage" permission should be set on a secret scope containing only those credentials that will be used by a given team.
B. "Read" permissions should be set on a secret scope containing only those credentials that will be used by a given team.
C. "Read'' permissions should be set on a secret key mapped to those credentials that will be used by a given team.
D. No additional configuration is necessary as long as all users are configured as administrators in the workspace where secrets have been added.
Solutions:
| Question 1 Answer: B | Question 2 Answer: D | Question 3 Answer: C | Question 4 Answer: D | Question 5 Answer: B |
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