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DEA-C01 Overview — Format, Domains & Who Should Take It

What to expect on AWS Certified Data Engineer — Associate (DEA-C01): exam format and timing, domain coverage and weights, question styles, recommended background, and an efficient study approach.

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Exam at a glance

  • Exam name: AWS Certified Data Engineer — Associate (DEA-C01)
  • Level: Associate
  • Questions: 65 total (multiple-choice and multiple-response)
  • Time: 130 minutes
  • Delivery: Pearson VUE testing center or online proctored exam
  • Result: Scaled score (100–1000); minimum passing score: 720
  • Cost: 150 USD
  • Languages offered: English, Japanese, Korean, Simplified Chinese

Tip: DEA-C01 is “end-to-end data platform” thinking: ingestion patterns, ETL choices, storage and modeling trade-offs, operations/monitoring, and security/governance.

Domain breakdown (weights)

  • Domain 1: Data Ingestion and Transformation — 34%
  • Domain 2: Data Store Management — 26%
  • Domain 3: Data Operations and Support — 22%
  • Domain 4: Data Security and Governance — 18%

What the exam emphasizes (high level)

Expect scenario-driven items where you choose the best answer for:

  • Ingesting data (batch + streaming), handling triggers/schedules, and designing replayable pipelines
  • Transforming and processing data using appropriate AWS services (and recognizing performance/cost trade-offs)
  • Selecting data stores, designing schemas, managing catalogs/partitions, and handling lifecycle policies
  • Monitoring and troubleshooting pipelines, ensuring data quality, and optimizing runtime/cost
  • Implementing authentication/authorization, encryption/masking, logging for audit, and privacy/governance controls

Who should take DEA-C01

This exam is a strong fit for:

  • Data engineers and analytics engineers building pipelines on AWS
  • Platform engineers supporting data lakes/warehouses and orchestration
  • Data architects who need a validated AWS-focused pipeline + governance skill set

Recommended background (AWS guidance):

  • ~2–3 years of experience in data engineering or data architecture
  • At least 1–2 years of hands-on experience with AWS services

Study plan (efficient)

  1. Pick a timeline: 30/60/90-day Study Plan →
  2. Work the Syllabus task-by-task; drill immediately after each task.
  3. Keep a miss log: convert misses into one-liner rules (“EventBridge for schedules + triggers”, “Lake Formation for fine-grained permissions”, “Parquet + partitions for Athena cost/perf”).
  4. Final 1–2 weeks: mixed sets + at least a couple timed runs; review every miss.
Study Plan