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Databricks Certified Data Engineer Associate — Requirements & Free Practice

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Databricks Certified Data Engineer Associate

Databricks certification validating foundational data engineering skills on its platform.

Licensing authority: Databricks

Initial by examination
Databricks Certified Data Engineer Associate
Eligibility
Applicants must be 18 years old or older. This exam has no additional prerequisite; related training is recommended. Certification status follows a passing exam result and Databricks proctor review.

Databricks Certified Data Engineer Associate

Provider
Kryterion
Format
Proctored multiple-choice
Exam questions
Total questions: 45–55; Scored questions: 45; Unscored questions: 0–10; The total includes the scored and unscored questions.
Time limit
90 minutes
Exam fee
USD 200, plus applicable taxes
Examination outline
  • Databricks Intelligence Platform (6%)
    • Core components of the Databricks Platform
    • Databricks Platform compute services
  • Data Ingestion and Loading (21%)
    • Data ingestion patterns and sources
    • COPY INTO incremental loading
    • Auto Loader schema enforcement and evolution
    • Lakeflow Connect configuration
    • JDBC/ODBC or REST clients in notebooks
    • Selecting ingestion methods
    • Semi-structured and unstructured data ingestion
  • Data Transformation and Modeling (22%)
    • Data cleaning with PySpark/SQL
    • Combining DataFrames
    • Manipulating columns, rows, and table structures
    • Deduplication and aggregation
    • Basic Spark tuning parameters
    • Gold layer objects
    • Data quality checks and validation rules
  • Working with Lakeflow Jobs (16%)
    • Control flows with Lakeflow Jobs
    • Lakeflow Jobs task configuration and dependencies
    • Lakeflow Jobs schedules and trigger types
    • Time-based and data-driven triggers
  • Implementing CI/CD (10%)
    • Code development workflow in Databricks workspace
    • Environment-specific bundle configuration
    • Declarative Automation Bundles deployment
    • Databricks CLI in CI/CD workflows
  • Troubleshooting, Monitoring, and Optimization (10%)
    • Job performance trends
    • Lakeflow Jobs UI pipeline health monitoring
    • Spark UI performance bottlenecks
    • Liquid Clustering and predictive optimization
    • Cluster startup, library, and memory failures
  • Governance and Security (15%)
    • Managed and external tables in Unity Catalog
    • Access controls and privileges
    • Column-level masking and row-level security
    • Unity Catalog ABAC policies
Examination sources