The AWS Certified Data Engineer - Associate (DEA-C01) validates your ability to design, build, and manage data pipelines, data lakes, and analytics solutions on AWS. This certification is designed for professionals who implement data engineering solutions using AWS services.
130 minutes
65 questions
720/1000
$150 USD
The DEA-C01 exam gives you 130 minutes for 65 questions, and you need 720/1000 to pass. Reading study notes does not tell you whether you would clear that bar today — only answering exam-style questions under the same conditions does.
Practice is most useful when it follows the exam blueprint rather than a random question bank. Data Ingestion and Transformation alone accounts for 34% of your DEA-C01 score, so a weak spot there costs you far more than an equivalent gap in a lighter domain. Practising by domain shows you where your points are actually leaking.
Answer 15 exam-style DEA-C01 questions in about 10 minutes. You will see your result broken down by domain and where your gaps are. No card required — create an account so your answers are saved.
Start free DEA-C01 practice examThe Data Engineer Associate exam focuses on building and managing data pipelines using AWS analytics services. Data ingestion and transformation is the largest domain at 34%, covering Kinesis (Data Streams, Firehose), AWS Glue (crawlers, jobs, ETL scripts, Data Catalog), EMR, and Step Functions for orchestrating data workflows. You'll need to understand when to use batch vs stream processing and how to design for both.
The data store management domain (26%) tests knowledge of S3 data lake architectures, DynamoDB, Redshift (including Serverless, Spectrum, and data sharing), RDS, and Lake Formation for centralized access control. Expect questions about data formats (Parquet, Avro, JSON, ORC), partitioning strategies, and data lifecycle management with S3 storage classes and Intelligent-Tiering.
Focus on AWS Glue and Kinesis — these two service families dominate the exam. Understand Glue crawlers, the Data Catalog, Glue ETL jobs (both visual and script-based), Glue job bookmarks for incremental processing, and Glue DataBrew for visual data preparation. For Kinesis, know the differences between Data Streams and Firehose, how to handle consumer lag, and how to scale shards.
Redshift is the other major topic: understand distribution styles (EVEN, KEY, ALL), sort keys, Redshift Spectrum for querying S3, and how to optimize query performance with VACUUM and ANALYZE. Lake Formation for data governance is tested throughout the security domain. Use practice exams to identify your weak spots and focus study time accordingly.
Data engineering is one of the fastest-growing roles in tech, and the AWS Data Engineer certification validates the skills employers need most: building scalable data pipelines, managing data lakes, and implementing analytics solutions. Certified AWS data engineers command salaries ranging from $130,000 to $170,000, and demand continues to outpace supply.
This certification is ideal for data engineers working primarily with AWS, ETL developers modernizing on-premises data warehouses, and analytics engineers building data platforms. It pairs well with the Solutions Architect Associate for a comprehensive cloud + data skill set, or with the Machine Learning Engineer Associate for data engineers expanding into ML.
Take a free 10-minute AI assessment to identify your knowledge gaps for the AWS Data Engineer Associate exam.
Start Free AssessmentThe DEA-C01 covers four domains: Data Ingestion and Transformation (34%), Data Store Management (26%), Data Operations and Support (22%), and Data Security and Governance (18%). The exam has 65 questions, takes 130 minutes, and requires a 720/1000 passing score.
The Data Engineer Associate is one of the more challenging associate-level exams because it covers a broad range of analytics services. You need deep knowledge of AWS Glue, Kinesis, Redshift, EMR, and Lake Formation. With 1-2 years of data engineering experience on AWS, most candidates need 4-6 weeks of study.
AWS Glue dominates the exam — master crawlers, the Data Catalog, ETL jobs, job bookmarks, and DataBrew. Kinesis (Data Streams vs Firehose) and Redshift (distribution styles, sort keys, Spectrum) are also heavily tested. Understand data formats (Parquet, Avro, ORC), S3 data lake patterns, and Lake Formation for governance.
Absolutely. Data engineering is one of the fastest-growing tech roles with salaries ranging from $130,000 to $170,000. The AWS Data Engineer certification validates in-demand skills in building data pipelines, managing data lakes, and implementing analytics solutions — skills that nearly every data-driven company needs.
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