Demand for Databricks-certified professionals keeps outpacing supply, and the Databricks Certified Data Engineer Associate exam is the doorway in. Actual4Exams stocks 322 practice questions built specifically for Databricks-Certified-Data-Engineer-Associate, so your preparation targets the credential employers are actually paying for.
Databricks Databricks-Certified-Data-Engineer-Associate Exam Overview:
| Certification Vendor: | Databricks |
|---|---|
| Exam Name: | Databricks Certified Data Engineer Associate Exam |
| Exam Number: | DE-A |
| Certificate Validity Period: | 2 years |
| Exam Price: | USD 200 |
| Related Certifications: | Databricks Certified Data Engineer Professional |
| Exam Format: | Multiple-choice, Proctored online or test center, Scenario-based questions |
| Available Languages: | English |
| Real Exam Qty: | 45 scored multiple-choice questions |
| Passing Score: | Approximately ~70% (not officially fixed/publicly guaranteed) |
| Exam Duration: | 90 minutes |
| Recommended Training: | Official Data Engineering with Databricks Course Databricks Data Engineering Learning Path (Databricks Academy) |
| Exam Registration: | Databricks Certification Portal |
| 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 Databricks-Certified-Data-Engineer-Associate Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Productionizing Data Pipelines | - Scheduling and monitoring jobs - Databricks Workflows / Jobs orchestration - Pipeline deployment and operationalization |
| Topic 2: Data Governance and Quality | - Unity Catalog basics - Data access control and governance - Data quality concepts and management |
| Topic 3: Databricks Lakehouse Platform Fundamentals | - Clusters, notebooks, and basic Databricks environment usage - Workspace, architecture, and core platform concepts |
| Topic 4: Data Ingestion and ELT Development | - Handling structured and semi-structured data - Data ingestion using Spark SQL and PySpark - ETL patterns and transformations |
| Topic 5: Data Processing and Transformations | - User-defined functions (UDFs) - Apache Spark SQL operations (joins, aggregations, filtering) - PySpark DataFrame transformations - Delta Lake fundamentals (tables, transactions, optimization) |
FAQ: Preparing for Databricks Certified Data Engineer Associate the Smart Way
Databricks Certified Data Engineer Associate is an official exam run by Databricks under exam code Databricks-Certified-Data-Engineer-Associate. Passing it awards the Databricks Certified Data Engineer Associate certification, which sits at the Associate tier. It also counts toward related credentials such as Databricks Certified Data Engineer Professional. Certified professionals remain in shorter supply than the market wants, which is precisely why this exam keeps showing up in conversations about better roles and better pay.
The Databricks Certified Data Engineer Associate exam gives you 90 minutes to work through 45 scored multiple-choice questions questions. That is a tight ratio, and it punishes candidates who get emotionally attached to any single item. The fix is mechanical: answer what you know, flag what you do not, and keep moving. A few full-length timed runs in the Actual4Exams test engine, with its randomized question order, will calibrate your pace far better than untimed reading ever could.
The official fee for Databricks Certified Data Engineer Associate is USD 200, and Approximately ~70% (not officially fixed/publicly guaranteed) is what passing takes. The uncomfortable part: retakes cost the full USD 200 again, which makes preparation the cheapest line item in this whole project. Before booking, put yourself through repeated scored sessions with the Actual4Exams practice tests and compare results over time; a stable margin above the passing line, not a single lucky run, is when you are ready.
No formal prerequisites required; recommended ~6 months hands-on experience with Databricks, Spark SQL, and PySpark.
Vendor rules do get revised, so treat this as your starting point and confirm the current eligibility details before booking via the official exam page.
Databricks Certified Data Engineer Associate registration runs through these official channels.
Worth noting when you schedule: the exam is delivered Online proctored exam or test center.
Yes, Databricks points Databricks Certified Data Engineer Associate candidates toward the following training.
- Databricks Data Engineering Learning Path (Databricks Academy)
- Official Data Engineering with Databricks Course
Whatever course you choose, close the loop with question practice: the 322 items in the Actual4Exams Databricks-Certified-Data-Engineer-Associate package convert course knowledge into exam-day scoring ability.
It is. Actual4Exams publishes a free PDF demo of the Databricks Certified Data Engineer Associate material, so the product can prove itself before you pay. Your purchase then comes with 365 days of free updates, and once that period ends, extending the update service costs 50% of the regular price. The test engine software itself is verified malware-free and safe to install.
Actual4Exams stands behind the product with a 100% money-back guarantee under defined conditions. If you take the Databricks Certified Data Engineer Associate exam within 60 days of purchase and fail, you qualify for a full refund, provided the exam corresponds to your product. Sitting the exam within 3 days of purchase does not qualify, and neither do unused downloads, free materials, or expired orders; the candidate name must match the payer name. Submit a scanned enrollment slip and the official Score Report PDF within 2 days of the exam, and claims are resolved within 7 days. You may also choose an exchange instead of a refund: two other exam products of equal value, free, with the update service on your original purchase retained.
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Databricks Certified Data Engineer Associate breaks down into 5 official domains, led by Databricks Lakehouse Platform Fundamentals, Data Processing and Transformations, and Data Ingestion and ELT Development. You will find the full topic-by-topic outline above on this page; use the weightings to budget your study hours where they pay back the most.
Databricks Certified Data Engineer Associate Sample Questions:
A data engineer is maintaining an ETL pipeline code with a GitHub repository linked to their Databricks account. The data engineer wants to deploy the ETL pipeline to production as a databricks workflow. Which approach should the data engineer use?
- A. Maintain workflow_config.json and deploy it using Terraform
- B. Maintain workflow_config.json and deploy it using Databricks CLI
- C. Databricks Asset Bundles (DAB) + GitHub Integration
- D. Manually create and manage the workflow in UI
Explanation: Only visible for Actual4Exams members. You can sign-up / login (it's free).
A data engineer is creating a Spark DataFrame transformation pipeline. The pipeline consists of multiple transformations such as filter, select, and join operations before writing results to a Delta table. Which Spark characteristic allows these transformations to be optimized before execution?
- A. Parallel processing
- B. Broadcasting
- C. Checkpointing
- D. Lazy evaluation
A data engineer wants to inspect the schema of a Spark DataFrame during development to understand column names and data types. Which DataFrame method prints the schema in a tree format?
- A. showSchema
- B. getSchema
- C. printSchema
- D. describeSchema
A data engineer is inspecting an ETL pipeline based on a Pyspark job that consistently encounters performance bottlenecks. Based on developer feedback, the data engineer assumes the job is low on compute resources. To pinpoint the issue, the data engineer observes the Spark UI and finds out the job has a high CPU time vs Task time. Which course of action should the data engineer take?
- A. High CPU time vs Task time means an under-utilized cluster. The data engineer may need to repartition data to spread the jobs more evenly throughout the cluster.
- B. High CPU time vs Task time means a CPU over-utilized job. The data engineer may need to consider executor and core tuning or resizing the cluster
- C. High CPU time vs Task time means over-utilized memory and the need to increase parallelism
- D. High CPU time vs Task time means efficient use of cluster and no change needed
Explanation: Only visible for Actual4Exams members. You can sign-up / login (it's free).
A data engineer wants to combine two datasets that share the same schema and append rows from one dataset to another. Which Spark DataFrame operation performs this row-wise combination?
- A. union
- B. intersect
- C. merge
- D. join
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