AWS Certified Data Engineer – Associate (DEA-C01)

About the DEA-C01 exam

AWS Certified Data Engineer – Associate is for people who build and run data pipelines on AWS: getting data in, reshaping it, storing it in the right place, keeping it secure and making sure the pipeline keeps working. AWS describes the target candidate as having the equivalent of two to three years of data engineering experience and at least one to two years of hands-on work with AWS.

The questions are scenarios from a data team's working week. A Glue job reprocesses files it already handled, a Kinesis stream has one hot shard, Athena queries cost too much because they scan the whole table, or analysts in another account need access to a subset of columns. You pick the fix that meets the requirement with the least effort or cost. Programming-language syntax and ML training are out of scope, but you are expected to read SQL and reason about how a pipeline behaves.

Exam format

• Questions: 65, multiple choice (one answer from four) or multiple response (two or more answers from five or more). 15 of the 65 are unscored trial questions, and they aren't identified.
• Time: 130 minutes.
• Passing score: 720 on a scaled score from 100 to 1,000.
• Cost: 150 USD, at a Pearson VUE test center or online with a remote proctor.
• Validity: 3 years.

What the exam covers

The official exam guide has four domains:

• Data Ingestion and Transformation (34%). Streaming with Kinesis Data Streams, Firehose and Amazon MSK; batch ingestion with DMS, AppFlow and S3 events; transformation with Glue, EMR and Managed Service for Apache Flink; and orchestration with Step Functions, MWAA and EventBridge.
• Data Store Management (26%). Choosing between S3, Redshift, DynamoDB and other stores; Redshift distribution and sort keys; partitioning and file formats such as Parquet and Apache Iceberg; the Glue Data Catalog and crawlers; and lifecycle rules for data that ages.
• Data Operations and Support (22%). Monitoring and alerting on failed jobs, tuning Athena and Redshift queries, data quality rules, and troubleshooting slow or broken pipelines.
• Data Security and Governance (18%). IAM and KMS for pipelines, Lake Formation permissions down to rows and columns, Macie for sensitive data, masking, and audit logging with CloudTrail.

AWS revised the exam guide to version 1.1 in December 2025, adding skills on vector indexes, connecting pipelines to large language models, open table formats, Amazon S3 Tables and Amazon SageMaker Catalog and Unified Studio.

How the practice questions here are organised

There are 10 practice tests of 10 questions each, and each test covers all four domains, with ingestion and transformation questions the most common, as on the real exam. Every question explains why the right answer works and why each other option falls short, with a link to the AWS documentation it comes from.

The full practice exam copies the real one: 65 questions in 130 minutes, weighted by domain the same way and written against version 1.1 of the guide, with answers hidden until you submit. It scores all 65 and passes you at 72%, because AWS doesn't publish how the scaled score maps to correct answers.

A study plan that works

• Take Test 1 cold to see which domains need work.
• Learn the Glue features by name: job bookmarks, crawlers, the Data Catalog, Data Quality and the Flex execution class each answer a specific kind of question.
• Know the main Redshift and Athena cost and speed levers, such as distribution and sort keys, partition projection, columnar formats and compacting small files.
• Be clear on when Lake Formation permissions apply instead of plain IAM and bucket policies, especially across accounts.
• Read every explanation, then sit the full practice exam timed once most tests pass comfortably.

These questions are original, written from the public AWS documentation and the official exam guide. They are not real exam questions, and this site is not affiliated with AWS.