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AWS DEA-C01 Guide: Data Engineer Associate

AWS DEA-C01 exam guide covering ingestion, transformation, data stores, operations, security, and governance decisions.

This guide is for candidates preparing for AWS Certified Data Engineer - Associate (DEA-C01) and for readers who need a sharper review of data lake, streaming, batch, orchestration, and governance patterns on AWS. The real exam is less about memorizing isolated services and more about designing data platforms that stay queryable, replayable, governed, and supportable under production pressure.

Data lake: Centralized storage pattern that keeps raw and curated data available for many analytics tools and downstream consumers.

Orchestration: Coordinating multi-step pipeline tasks, dependencies, retries, and scheduling.

Backfill: Reprocessing historical data to load missing, corrected, or newly required records into a pipeline.

Current orientation

AWS positions DEA-C01 as an associate-level certification for candidates with roughly 2-3 years of data engineering experience and at least 1-2 years of hands-on AWS work. The current exam uses 65 questions over 130 minutes, and AWS reports the passing score as 720.

AWS’s current exam guide breaks DEA-C01 into four weighted domains, and this online guide now follows that structure directly:

What strong answers usually do

  • land data durably first, then optimize transformation and serving layers around that landing pattern
  • separate ingestion choice from storage choice and analytics choice instead of trying to solve everything with one service
  • design for replay, late data, duplicates, schema drift, and monitoring rather than assuming the happy path
  • treat governance as part of the platform design, not as an afterthought added after pipelines already exist

Use this exam guide in order

  • Start with the study plan if you want a practical weekly sequence.
  • Work through the four weighted domain chapters in order, starting with Data Ingestion and Transformation and Data Store Management.
  • Use the cheat sheet for high-yield service pickers and trade-offs after you know the chapter logic.
  • Use the cheat sheet when pipeline, governance, replay, and query-path decisions start to blur.
  • Work through the sample questions to practice data-platform design prompts with full explanations.
  • Keep the glossary open when lakehouse, streaming, and metadata terms begin to blur together.
  • Use the FAQ to calibrate expected depth and exam fit.
  • Keep the resources page nearby while you work through the official AWS exam guide and primary service docs.

Coverage map against the current exam guide

Domain Weight What to study first
1. Data Ingestion and Transformation 34% 1.1 Ingestion Patterns, Sources & Triggers, 1.2 Transformation Services, Formats & Processing Trade-Offs, 1.3 Orchestration, Workflows & Notifications, 1.4 Programming, IaC & Code Performance
2. Data Store Management 26% 2.1 Choosing Data Stores for Access Patterns, 2.2 Catalogs, Crawlers & Metadata, 2.3 Data Lifecycle, Loads & Retention, 2.4 Data Models, Schema Evolution & Optimization
3. Data Operations and Support 22% 3.1 Automation, Data APIs & Query Operations, 3.2 Analysis, Visualization & SQL Patterns, 3.3 Monitoring, Logging & Pipeline Troubleshooting, 3.4 Data Quality, Consistency & Skew
4. Data Security and Governance 18% 4.1 Authentication, Secrets & Network Access, 4.2 Authorization, Least Privilege & Lake Formation, 4.3 Encryption, Masking & Cross-Account Protection, 4.4 Logging, Privacy, Sovereignty & Governance

Review flow

    flowchart LR
	  A["Study plan"] --> B["1. Ingestion and transformation"]
	  B --> C["2. Data stores and metadata"]
	  C --> D["3. Operations and support"]
	  D --> E["4. Security and governance"]
	  E --> F["Cheat sheet, glossary, and final review"]

In this section

Revised on Sunday, May 10, 2026
SOA-C03
MLA-C01