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    Free Practice Questions for Cloudera Data Engineer (CDP-3002) Certification

    🔄 Last checked for updates August 7th, 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)

    Official study guide

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    Question formats CertSafari offers
    • Multiple choice
    passing score:

    55%

    delivery method:

    online, proctored

    target audience:

    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.

    allowed resources:

    none

    time limit minutes:

    90

    number of questions:

    50

    Exam Topics & Skills Assessed

    Skills measured (from the official study guide)

    Domain 1: Spark

    Subdomain 1.1: Fundamentals on Spark over Kubernetes

    Fundamentals on Spark over Kubernetes

    Subdomain 1.2: Work with DataFrames

    Work with DataFrames

    Subdomain 1.3: Understand Distribute Processing

    Understand Distribute Processing

    Subdomain 1.4: Implement Hive and Spark Integration

    Implement Hive and Spark Integration

    Subdomain 1.5: Understand Distributed Persistence

    Understand Distributed Persistence

    Domain 2: Airflow

    Subdomain 2.1: Implement incremental extraction in Apache Airflow from source system

    Implement incremental extraction in Apache Airflow from source system

    Subdomain 2.2: Use Apache Airflow to schedule ETL pipelines

    Use Apache Airflow to schedule ETL pipelines

    Subdomain 2.3: Use Apache Airflow to schedule quality checks

    Use Apache Airflow to schedule quality checks

    Subdomain 2.4: Work with DAGs

    Work with DAGs

    Domain 3: Performance Tuning

    Subdomain 3.1: Know Basic tools in (Spark) Performance Tuning

    Know Basic tools in (Spark) Performance Tuning

    Subdomain 3.2: Understand Optimization Framework and Explain plans

    Understand Optimization Framework and Explain plans

    Subdomain 3.3: Understand Inferring Schemas

    Understand Inferring Schemas

    Subdomain 3.4: Work with Improving Join Performance Leverage Caching Data for Reuse

    Work with Improving Join Performance Leverage Caching Data for Reuse

    Subdomain 3.5: Work with Partitioned and Bucketed Tables

    Work with Partitioned and Bucketed Tables

    Domain 4: Deployment

    Subdomain 4.1: Use the API and CLI

    Use the API and CLI

    Subdomain 4.2: Work in the Data Engineering Service

    Work in the Data Engineering Service

    Domain 5: Iceberg

    Subdomain 5.1: Understand Iceberg

    Understand Iceberg

    Techniques & products

    Kubernetes
    DataFrames
    Hive
    Spark
    Apache Airflow
    ETL pipelines
    DAGs
    Spark UI
    Catalyst optimizer
    Cloudera Data Platform API
    CLI
    Apache Iceberg
    broadcast joins
    caching
    partitioned tables
    bucketed tables

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