AWS Certified Data Engineer - Associate (DEA-C01) Practice Tests

Use this DEA-C01 practice exam to prepare for AWS Certified Data Engineer - Associate (DEA-C01) with realistic questions, detailed explanations, and focused study modes. The practice bank includes 1,120 questions for AWS DEA-C01, so you can review the exam steadily instead of relying on one long cram session.

As you practice, pay extra attention to recurring topics such as Data Ingestion and Transformation, Data Store Management, Data Operations and Support, and Data Security and Governance. Start with short sessions to identify weak areas, then move into timed quizzes once your accuracy is consistent.

The explanations are especially useful when you want to connect exam wording to the responsibilities and scenarios described in the official certification guidance. Use the free preview first, then unlock the full question bank when you are ready to build a complete study routine.

The AWS Certified Data Engineer – Associate (DEA-C01) is an associate-level credential that validates a practitioner's ability to implement, monitor, and optimize data pipelines on AWS. Launched in 2023, it is the first AWS certification designed specifically for data engineers, replacing the need to cobble credentials from Solutions Architect or Data Analytics Specialty exams. The exam assesses proficiency across the full data engineering lifecycle: ingesting and transforming data, selecting and managing appropriate data stores, orchestrating pipelines using programming concepts, and enforcing data security and governance policies using AWS-native tooling.

Key AWS services in scope include Amazon S3, AWS Glue, Amazon Redshift, Amazon Kinesis, Amazon EMR, AWS Lake Formation, Amazon DynamoDB, AWS Database Migration Service, and Amazon Athena, among others. Candidates are evaluated on their ability to compare cost and performance trade-offs between services, apply SQL on AWS platforms, implement encryption and access controls, and validate data quality and consistency. Out-of-scope topics include ML model training and inference, programming-language-specific syntax, and deriving business conclusions from data analysis.

The target candidate is a data engineer or data architect with roughly 2–3 years of experience in data engineering and at least 1–2 years of hands-on AWS experience. This includes professionals who design and maintain ETL/ELT pipelines, manage data lakes and warehouses, or work with real-time streaming architectures. Adjacent roles transitioning into cloud data engineering — such as database administrators, backend developers, or traditional ETL developers — will also find this certification a clear roadmap for bridging legacy skills with AWS-native approaches.

The exam suits those who regularly work with concepts such as volume, variety, and velocity of data; data modeling and schema design; data lifecycle management; and cloud security and governance. It is not aimed at data scientists, ML engineers, or business analysts, as those domains fall outside the exam's scope.

AWS does not enforce formal prerequisites for the DEA-C01, but the official exam guide recommends 2–3 years of data engineering or data architecture experience and 1–2 years of hands-on work with AWS services. Candidates should be comfortable setting up and maintaining ETL pipelines from ingestion to destination, writing and executing SQL queries, using Git-based source control workflows, and applying language-agnostic programming concepts (loops, conditionals, data structures).

On the AWS side, recommended knowledge includes familiarity with data pipeline orchestration services (AWS Glue, AWS Step Functions), storage systems (Amazon S3, Amazon Redshift, Amazon DynamoDB), streaming platforms (Amazon Kinesis), and security/governance services (AWS IAM, AWS KMS, AWS Lake Formation). Understanding of data lakes, networking fundamentals (VPC, subnets, connectivity), compute options (Amazon EMR, AWS Lambda), and vector/embedding concepts is also beneficial. While no prior AWS certification is required, having the AWS Cloud Practitioner or AWS Solutions Architect – Associate background provides a useful foundation.

The DEA-C01 exam consists of 65 total questions: 50 scored questions that contribute to the final result and 15 unscored pilot questions that AWS uses to evaluate future content. Unscored questions are not identified, so candidates should treat all questions equally. Question types are multiple choice (one correct answer from four options) and multiple response (two or more correct answers from five or more options). The time limit is 130 minutes, and the exam is delivered via Pearson VUE at a testing center or through an online proctored session. The exam is available in English, Japanese, Korean, and Simplified Chinese, and costs $150 USD.

Scores are reported on a scaled range of 100–1,000, and the minimum passing score is 720. AWS uses a compensatory scoring model, meaning candidates do not need to achieve a passing threshold in each individual domain — only the overall scaled score matters. Unanswered questions are treated as incorrect; there is no penalty for guessing. The certification is valid for three years, after which recertification requires passing the current version of the exam.

The DEA-C01 certification targets one of the fastest-growing roles in cloud computing. AWS-certified data engineers in the US report average salaries around $141,000 per year according to Glassdoor data, with entry-level positions starting near $124,000–$130,000 and senior roles exceeding $175,000. Research from the Jefferson Frank Careers and Hiring Guide found that 73% of AWS professionals saw a salary increase after certification, averaging approximately 27%. Job roles accessible with this credential include Data Engineer, Cloud Data Architect, ETL/ELT Developer, Data Platform Engineer, and Analytics Engineer.

AWS certifications appear in cloud job postings more than any other vendor credential, and the DEA-C01 specifically validates the services — Glue, Redshift, Kinesis, S3 — that dominate real-world data engineering job requirements. For professionals transitioning from database administration, backend development, or traditional ETL roles, the certification provides a structured path into cloud-native data engineering. Many candidates report role transitions or salary increases within 3–6 months of earning the credential. Pairing DEA-C01 with the Databricks Data Engineer Associate certification is widely considered the most job-market-relevant two-certification combination in the data engineering space.