2025: Databricks Data Engineer Professional Practice Exams

The Databricks Certified Data Engineer Professional certification exam assesses an individual’s ability to use Databricks to perform advanced data engineering tasks. This includes an understanding of the Databricks platform and developer tools like Apache Spark™, Delta Lake, MLflow, and the Databricks CLI and REST API. It also assesses the ability to build optimized and cleaned ETL pipelines. Additionally, the ability to model data into a lakehouse using knowledge of general data modeling concepts will be assessed. Finally, being able to ensure that data pipelines are secure, reliable, monitored and tested before deployment will also be included in this exam. Individuals who pass this certification exam can be expected to complete advanced data engineering tasks using Databricks and its associated tools.

The exam covers:

1. Databricks Tooling – 20%

2. Data Processing – 30%

3. Data Modeling – 20%

4. Security and Governance – 10%

5. Monitoring and Logging – 10%

6. Testing and Deployment – 10%

Assessment Details

Type: Proctored certification

Total number of questions: 60

Time limit: 120 minutes

Registration fee: $200

Question types: Multiple choice

Test aides: None allowed

Languages: English

Delivery method: Online proctored

Prerequisites: None, but related training highly recommended

Recommended experience: 1+ years of hands-on experience performing the data engineering tasks outlined in the exam guide

Validity period: 2 years

Recertification: Recertification is required to maintain your certification status. Databricks Certifications are valid for two years from issue date.

Unscored content: Exams may include unscored items to gather statistical information for future use. These items are not identified on the form and do not impact your score. Additional time is factored into the exams to account for this content.

What you’ll learn

• Practice with Realistic Scenarios: Solve a comprehensive set of practice exams that mirror the format and difficulty level of the actual certification exam.

• Identify Knowledge Gaps: Through the practice exams and detailed answer explanations, students will be able to pinpoint areas where they need further study.

• Sharpen Exam-Taking Skills: Help students develop effective test-taking strategies like time management, understand question intent & selecting the best answer

• Master Exam Content: Gain deep familiarity with the core concepts tested in the Databricks Professional Data Engineer certification exam.

Are there any course requirements or prerequisites?

• Basic Understanding of Data Engineering: Familiarity with core data engineering concepts like data ingestion, transformation, quality checks, and data storage.

• Exposure to Big Data Technologies: A general understanding of big data processing and distributed computing paradigms (optional but helpful).

• Prior Experience with Databricks (Preferred): While not mandatory, having some prior experience working with the Databricks platform would be beneficial. This could include experience with creating notebooks, working with clusters, or basic Apache Spark operations in Databricks.

Who this course is for:

• Data Engineers Seeking Certification: You're a data engineer with a solid foundation in the field and are aiming to validate your expertise with the Databricks Professional Data Engineer certification. You have experience working with data pipelines, data processing tools, and potentially some exposure to Databricks.

• Databricks Users Preparing for the Exam: You're a current Databricks user looking to enhance your proficiency with the platform and demonstrate your knowledge through the certification. You understand core Databricks functionalities and want to solidify your understanding of exam-relevant topics.

• Anyone Aiming to Bolster Databricks Skills: Even without immediate certification goals, you're a data professional who wants to strengthen your Databricks expertise and practice applying it to realistic data engineering scenarios.

• This course is NOT for: Complete beginners with no prior data engineering or Databricks experience. While we strive to be accessible, foundational knowledge would be beneficial.