Free Practice Questions for Cloudera Data Engineer (CDP-3002) Certification
- Guide checked for updates:
- 19 Sep 2026
- Question bank created:
- 7 Jul 2026
- Question bank last updated:
- 23 Sep 2026
Study with 340 exam-style practice questions designed to help you prepare for the Cloudera Data Engineer (CDP-3002).
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Exam Details
Key information about Cloudera Data Engineer (CDP-3002)
- Multiple choice
55%
online, proctored
Data Engineer professional, who knows how to work proficiently designing, developing and optimizing data workflows using Cloudera tools. Strong grasp of data modeling for efficient storage, including formats, partitioning and schema design, and Apache Iceberg. Expertise in performance optimization, bottleneck identification, query tuning and resource efficiency. Proficient in security configuration, monitoring, troubleshooting and cloud integration for Cloudera clusters using mainly Spark and Airflow.
none
90
50
Exam Topics & Skills Assessed
Skills measured (from the official study guide)
1: Spark
1.1: Fundamentals on Spark over Kubernetes
Fundamentals on Spark over Kubernetes
1.2: Work with DataFrames
Work with DataFrames
1.3: Understand Distribute Processing
Understand Distribute Processing
1.4: Implement Hive and Spark Integration
Implement Hive and Spark Integration
1.5: Understand Distributed Persistence
Understand Distributed Persistence
2: Airflow
2.1: Implement incremental extraction in Apache Airflow from source system
Implement incremental extraction in Apache Airflow from source system
2.2: Use Apache Airflow to schedule ETL pipelines
Use Apache Airflow to schedule ETL pipelines
2.3: Use Apache Airflow to schedule quality checks
Use Apache Airflow to schedule quality checks
2.4: Work with DAGs
Work with DAGs
3: Performance Tuning
3.1: Know Basic tools in (Spark) Performance Tuning
Know Basic tools in (Spark) Performance Tuning
3.2: Understand Optimization Framework and Explain plans
Understand Optimization Framework and Explain plans
3.3: Understand Inferring Schemas
Understand Inferring Schemas
3.4: Work with Improving Join Performance Leverage Caching Data for Reuse
Work with Improving Join Performance Leverage Caching Data for Reuse
3.5: Work with Partitioned and Bucketed Tables
Work with Partitioned and Bucketed Tables
4: Deployment
4.1: Use the API and CLI
Use the API and CLI
4.2: Work in the Data Engineering Service
Work in the Data Engineering Service
5: Iceberg
5.1: Understand Iceberg
Understand Iceberg
Techniques & products