The cost of the Databricks-Certified-Data-Engineer-Professional exam itself is high enough that nobody wants to pay it twice. If you worry about wasting time and money on a failed attempt, the Databricks Certified Data Engineer Professional materials at PracticeVCE exist for exactly that concern — thorough preparation, verified answers, and a written refund policy behind it all.
Databricks Databricks-Certified-Data-Engineer-Professional Exam Overview:
| Certification Vendor: | Databricks |
|---|---|
| Exam Name: | Databricks Certified Data Engineer Professional Exam |
| Exam Number: | Databricks-Certified-Data-Engineer-Professional |
| Certificate Validity Period: | 2 years |
| Passing Score: | 70 |
| Related Certifications: | Databricks Certified Data Engineer Associate |
| Exam Duration: | 120 minutes |
| Exam Format: | Multiple-response, Multiple-choice |
| Real Exam Qty: | 60 |
| Exam Price: | USD 200 |
| Available Languages: | English |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored |
| Pre Condition: | Databricks Certified Data Engineer Associate certification |
| Official Syllabus URL: | https://www.databricks.com/learn/certification/data-engineer-professional |
Databricks Databricks-Certified-Data-Engineer-Professional Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Modeling and Storage | 20% | - File Formats - Storage Optimization - Data Modeling |
| Monitoring and Troubleshooting | 16% | - Performance Optimization - Monitoring - Troubleshooting |
| Data Quality and Governance | 12% | - Data Lineage - Data Quality - Governance |
| Databricks Lakehouse Platform | 24% | - Lakehouse Architecture - Data Management - Delta Lake - Unity Catalog |
| Data Processing | 28% | - Data Transformation - ETL Pipelines - Structured Streaming - Spark SQL |
Databricks-Certified-Data-Engineer-Professional Exam Details and Product Questions
The Databricks-Certified-Data-Engineer-Professional exam contains 60 questions with 120 minutes minutes to complete them. The PC test engine and the online test engine both let you rehearse under the same time pressure, so pacing stops being a variable on exam day.
Databricks Certified Data Engineer Associate certification
Passing the Databricks-Certified-Data-Engineer-Professional exam requires 70, and registration costs USD 200. That fee is exactly why candidates worry about wasting money on a failed attempt — and why structured preparation with verified answers is worth more than hopeful improvisation.
Same Databricks Certified Data Engineer Professional content, different reach. The PC test engine runs on Windows, simulates the formal exam atmosphere, and shows you where your shortcomings and strengths lie — with no limit on the number of computers you install it on. The online test engine is available only at PracticeVCE: it runs on Windows, Mac, Android, and iOS, and once loaded it works without internet, so you can practice the Databricks-Certified-Data-Engineer-Professional exam questions on any device, at any time, anywhere. Both are built from the same daily-checked question bank.
The official outline divides the Databricks-Certified-Data-Engineer-Professional exam into weighted domains, including:
- Databricks Lakehouse Platform (24%)
- Data Quality and Governance (12%)
- Data Processing (28%)
The Databricks Certified Data Engineer Professional practice questions at PracticeVCE follow these same objectives across all three formats — PDF, PC engine, and online engine.
Work with your constraints, not against them. Short, regular sessions beat rare marathon ones: run a timed mock early to map your shortcomings, then spend your limited hours on those weak areas using the expert-verified answers to close each gap. The Databricks-Certified-Data-Engineer-Professional exam bank is organized around the official objectives, so nothing you study is off-topic — and the online engine turns commutes and queues into usable Databricks Certified Data Engineer Professional practice time.
The Databricks-Certified-Data-Engineer-Professional exam is the official assessment behind the Databricks Certified Data Engineer Professional certification from Databricks. Many candidates come to it at a career plateau, looking for a credential that demonstrates verified, practical command of the published objectives. The exam rewards preparation — and preparation is the one part of the process fully under your control.
Databricks Certified Data Engineer Professional Sample Questions:
The data engineer is using Spark's MEMORY_ONLY storage level. Which indicators should the data engineer look for in the spark UI's Storage tab to signal that a cached table is not performing optimally?
- A. The RDD Block Name included the '' annotation signaling failure to cache
- B. Size on Disk is < Size in Memory
- C. Size on Disk is> 0
- D. The number of Cached Partitions> the number of Spark Partitions
- E. On Heap Memory Usage is within 75% of off Heap Memory usage
Correct Answer: C 🗳️
Explanation: Only visible for PracticeVCE members. You can sign-up / login (it's free).
A data engineer is using the AUTO CDC API in Lakeflow Spark Declarative Pipeline to propagate deletions from a source table (orders_source) to a target table (orders_target). The source has Change Data Feed (CDF) enabled, but some delete events arrive out of order due to upstream delays. How does the AUTO CDC API internally ensure deletions are applied correctly despite out-of-order events?
- A. It manually sorts incoming events by timestamp before applying changes.
- B. It uses sequence_by to order events and retains tombstones for deleted rows until older sequences are processed.
- C. It runs VACUUM on the target table to purge conflicting records.
- D. It ignores deletions if they arrive after updates for the same key.
Correct Answer: B 🗳️
Explanation: Only visible for PracticeVCE members. You can sign-up / login (it's free).
A table 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 finishes.
- B. 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.
- C. The versions of each source table will be stored in the table transaction log; query results will be saved to DBFS with each query.
- D. Results will be computed and cached when the table is defined; these cached results will incrementally update as new records are inserted into source tables.
- E. 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.
Correct Answer: B 🗳️
Explanation: Only visible for PracticeVCE members. You can sign-up / login (it's free).
A data engineer needs to design an efficient pipeline that automatically processes new CSV files as they arrive in S3 storage. Which Databricks feature should the data engineer use to meet these requirements?
- A. Auto Loader with schema inference and evolution enabled
- B. COPY INTO SQL command with parameters to track processed files
- C. Traditional batch processing with scheduled Databricks Jobs
- D. Streaming from cloud storage using standard Spark readStream with format ("csv") and format ("json")
Correct Answer: A 🗳️
Explanation: Only visible for PracticeVCE members. You can sign-up / login (it's free).
A data engineer is designing a system to process batch patient encounter data stored in an S3 bucket, creating a Delta table (patient_encounters) with columns encounter_id, patient_id, encounter_date, diagnosis_code, and treatment_cost. The table is queried frequently by patient_id and encounter_date, requiring fast performance. Fine-grained access controls must be enforced. The engineer wants to minimize maintenance and boost performance. How should the data engineer create the patient_encounters table?
- A. Create an external table in Unity Catalog, specifying an S3 location for the data files. Enable predictive optimization through table properties, and configure Unity Catalog permissions for access controls.
- B. Create a managed table in Unity Catalog. Configure Unity Catalog permissions for access controls, schedule jobs to run OPTIMIZE and VACUUM commands daily to achieve best performance.
- C. Create a managed table in Hive Metastore. Configure Hive Metastore permissions for access controls, and rely on predictive optimization to enhance query performance and simplify maintenance.
- D. Create a managed table in Unity Catalog. Configure Unity Catalog permissions for access controls, and rely on predictive optimization to enhance query performance and simplify maintenance.
Correct Answer: D 🗳️
Explanation: Only visible for PracticeVCE members. You can sign-up / login (it's free).
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