Validate your ability to design and implement data pipelines on AWS. This exam covers data ingestion, transformation, orchestration, data store management, operations, monitoring, and data security and governance.
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Every in-scope ingestion, transformation, storage and governance service the DEA-C01 exam actually tests — organised by the four exam domains with decision tables and runbooks
The AWS Certified Data Engineer - Associate (DEA-C01) validates your ability to design, build, and maintain data pipelines on AWS. It covers data ingestion, transformation, orchestration, data store management, operations, monitoring, and data security and governance. This is one of the newer AWS certifications, launched to meet the growing demand for specialized data engineering skills.
This exam is designed for data engineers with 2-3 years of experience building and managing data pipelines on AWS. You should be comfortable writing SQL and Python/PySpark, working with services like Glue, Kinesis, Redshift, Athena, and S3, and understanding streaming vs. batch architectures. It's also suitable for analytics engineers, ETL developers, and data platform engineers looking to validate their AWS skills.
The DEA-C01 exam consists of 65 questions (50 scored, 15 unscored) in multiple-choice and multiple-response format. You have 130 minutes to complete the exam, and the passing score is 720 out of 1000 (approximately 72%). The exam is available at Pearson VUE testing centers and as an online proctored exam. The cost is $150 USD.
Recommended experience: 2-3 years of data engineering experience with at least 1-2 years of hands-on AWS experience. Familiarity with ETL pipelines, SQL, data lake architectures, and at least one streaming technology (Kinesis or Kafka).
The DEA-C01 is considered moderately difficult — harder than Cloud Practitioner but comparable to Solutions Architect Associate. The challenge is the breadth of services you need to know (Glue, Kinesis, Redshift, Athena, EMR, Lake Formation, DMS, and more) and the depth of data pipeline design scenarios. If you have production data engineering experience on AWS, 3-4 weeks of focused study is typically enough.
The exam heavily tests AWS Glue (ETL jobs, crawlers, Data Catalog, DataBrew, Data Quality), Amazon Kinesis (Data Streams, Firehose, Managed Flink), Amazon Redshift (COPY, Spectrum, data sharing), Amazon S3 (lifecycle, partitioning, formats), Amazon Athena, AWS Lake Formation, and AWS DMS. Understanding when to use each service and how they integrate is more important than memorizing individual features.
It's not required, but recommended. The DEA-C01 assumes familiarity with core AWS services like IAM, VPC, S3, and Lambda. If you already have production AWS experience, you can attempt it directly. Otherwise, starting with Solutions Architect Associate builds the foundational knowledge that makes the Data Engineer exam more approachable.
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