Databricks’ current exam guide for the Certified Data Engineer Associate covers the exam version as of 4 May 2026. Here is the format, the seven official sections and their weights, what Databricks recommends before you sit it, and a study plan based on the weights.
The exam at a glance
- Length: 45 scored multiple-choice questions in 90 minutes
- Unscored questions: the exam may include unscored items that are not identified. Databricks adds extra time to allow for them
- Fee: USD 200, plus applicable taxes as required by local law
- Delivery: proctored, online or at a test centre. No test aids are allowed
- Languages: English, Japanese, Brazilian Portuguese and Korean
- Code: the certification page says data manipulation code is shown in SQL when possible, and otherwise in Python
- Validity: 2 years. To recertify, you take the current version of the exam
Databricks does not state a pass mark on the certification page or in the exam guide.
The seven official sections
| Section | Weight |
|---|---|
| Data Transformation and Modeling | 22% |
| Data Ingestion and Loading | 21% |
| Working with Lakeflow Jobs | 16% |
| Governance and Security | 15% |
| Implementing CI/CD | 10% |
| Troubleshooting, Monitoring, and Optimization | 10% |
| Databricks Intelligence Platform | 6% |
The guide uses current product names. If your study material is older, note that Git folders were formerly Databricks Repos and Declarative Automation Bundles were formerly Databricks Asset Bundles.
Recommended experience and training
No prerequisite is required. The two official sources word the recommendation differently:
- Exam guide (PDF): course attendance and six months of hands-on experience in Databricks are highly recommended
- Certification page: related training is highly recommended, along with hands-on experience performing the data engineering tasks outlined in the exam guide
The exam guide lists the instructor-led course Data Engineering with Databricks, plus six self-paced courses in Databricks Academy covering Lakeflow Connect, Lakeflow Jobs, DevOps essentials, Unity Catalog interoperability, Lakeflow Spark Declarative Pipelines and data governance.
A study plan by weight
Ingestion and transformation together make up 43% of the exam. If you have about 40 hours, a split that follows the weights is roughly:
- 9 hours: Data Transformation and Modeling
- 8 hours: Data Ingestion and Loading
- 6 hours each: Working with Lakeflow Jobs, and Governance and Security
- 4 hours each: Implementing CI/CD, and Troubleshooting, Monitoring, and Optimization
- 3 hours: Databricks Intelligence Platform
What to practise hands-on
The exam guide’s objectives are practical, so try each of these in a workspace:
- load files incrementally with COPY INTO and Auto Loader, including schema enforcement and schema evolution
- clean bronze tables into silver tables with PySpark or SQL: joins, unions, exploding arrays, deduplication and aggregations
- build gold-layer objects such as materialized views, views and streaming tables
- set up Lakeflow Jobs with retries, conditional tasks and the three trigger types: scheduled, file arrival and table update
- deploy a bundle with the Databricks CLI, using variables and overrides for dev, test and prod
- spot data skew, shuffling and disk spilling in the Spark UI
- in Unity Catalog, compare managed and external tables, and apply GRANT, REVOKE and DENY, column masks and row-level security
Before you book, read the latest exam guide on Databricks’ Data Engineer Associate page. Databricks updates it whenever the exam changes.
I run ExamCrest, where this post first appeared. If you're preparing for Databricks Data Engineer Associate, there are 10 free Databricks Data Engineer Associate practice questions, each with the answer and a full explanation.
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