Databricks Databricks-Certified-Data-Engineer-Associate Questions & Answers - in .pdf
- Total Q&A: 322
- Update: Oct 13, 2026
- Price: $59.99
- Vendor: Databricks
- Exam Code: Databricks-Certified-Data-Engineer-Associate
- Exam Name: Databricks Certified Data Engineer Associate Exam
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- Total Q&A: 322
- Update: Oct 13, 2026
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- Vendor: Databricks
- Exam Code: Databricks-Certified-Data-Engineer-Associate
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Databricks Databricks-Certified-Data-Engineer-Associate Exam Syllabus Topics:
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Reference: https://www.databricks.com/learn/certification/data-engineer-associate
Databricks Databricks-Certified-Data-Engineer-Associate Exam Overview:
| Certification Vendor: | Databricks |
|---|---|
| Exam Name: | Databricks Certified Data Engineer Associate Exam |
| Exam Number: | DE-A |
| Available Languages: | English |
| Exam Format: | Proctored online or test center, Multiple-choice, Scenario-based questions |
| Exam Duration: | 90 minutes |
| Passing Score: | Approximately ~70% (not officially fixed/publicly guaranteed) |
| Certificate Validity Period: | 2 years |
| Real Exam Qty: | 45 scored multiple-choice questions |
| Related Certifications: | Databricks Certified Data Engineer Professional |
| Exam Price: | USD 200 |
| Recommended Training: | Databricks Data Engineering Learning Path (Databricks Academy) Official Data Engineering with Databricks Course |
| Exam Registration: | Databricks Certification Portal |
| Sample Questions: | Databricks Databricks-Certified-Data-Engineer-Associate Sample Questions |
| Exam Way: | Online proctored exam or test center |
| Pre Condition: | No formal prerequisites required; recommended ~6 months hands-on experience with Databricks, Spark SQL, and PySpark. |
| Official Syllabus URL: | https://www.databricks.com/learn/certification/data-engineer-associate |
Databricks Certified Data Engineer Associate Sample Questions:
Question #1
A data engineering team is building a new data transformation notebook. During development, they need fast testing, quick code changes, and easy debugging. Later, the notebook will run nightly as a scheduled job without human intervention. They want to optimize for development speed. Which compute should they use during development?
A. Use classic job compute.
B. Use SQL warehouses.
C. Use interactive compute.
D. Use instance pools.
Question #2
A team is designing their Data bricks Asset Bundle for deployment. They want to ensure their bundle includes all necessary resources, targeted environment configurations, and deployment settings in a single version-controlled file. What is required as the main configuration file at the root of their project?
A. A Python script called configure_bundle.py that dynamically creates resources at runtime
B. A databricks.yml YAML file that contains the bundle's name, targets, includes resources, and variables
C. A directory with multiple TXT files, each describing a single resource for the bundle
D. A JSON file named bundle_config.json that stores all resource details and environment variables
Question #3
A data engineer needs to create a table in Databricks using data from their organization's existing SQLite database.
They run the following command:
Which of the following lines of code fills in the above blank to successfully complete the task?
A. autoloader
B. DELTA
C. org.apache.spark.sql.jdbc
D. org.apache.spark.sql.sqlite
E. sqlite
Question #4
A developer has configured Databricks Connect and starts running PySpark code locally. They notice that Data Frame operations are executed on the remote cluster, but actions like .show() return results directly in their local console. What does this behaviour illustrate about how Databricks Connect is used?
A. It runs all Spark compute locally and only reads remote files
B. It requires manual synchronization of results from the cluster
C. It proxies Spark commands from the local client to the remote cluster
D. It mirrors the entire cluster environment on the developer's machine
Question #5
A data engineer wants to create an external table in Databricks that references data stored in an Azure Data Lake Storage (ADLS) location. The goal is to enable Databricks to access and query this external data without moving it into the Databricks-managed storage. Which step should the data engineer take to successfully create the external table?
A. Use the CREATE MANAGED TABLE statement and specify the LOCATION clause with the path to the external data.
B. Use the CREATE TABLE statement and specify the LOCATION clause with the path to the external data.
C. CREATE EXTERNAL TABLE statement without specifying a LOCATION clause.
D. CREATE UNMANAGED TABLE statement without specifying a LOCATION clause.
Solutions:
| Question #1 Correct Answer: C | Question #2 Correct Answer: B | Question #3 Correct Answer: C | Question #4 Correct Answer: C | Question #5 Correct Answer: B |
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