- What the DEA-C01 Certification Actually Is
- Exam Format, Fee and Scoring at a Glance
- The Four Content Domains and What They Test
- How the Questions Are Written
- Who Should Sit the Exam
- Eligibility, Booking and Test-Day Rules
- Scope Details That Trip Up Candidates
- Careers, Hiring and Career Value
- Validity and Renewal
- Sequencing Your Preparation Around the Weights
- Frequently Asked Questions
- DEA-C01 is the AWS Certified Data Engineer - Associate exam: 65 questions, 130 minutes, USD 150, delivered through Pearson VUE.
- You need a scaled score of 720 on a 100-1,000 scale; this is not a 72% raw-score cutoff.
- Data Ingestion and Transformation carries 34% of scored content, making it the biggest domain.
- No prerequisite certification is required; the two-to-three years of experience figure is guidance, not an admission rule.
What the DEA-C01 Certification Actually Is
DEA-C01 is the exam code for the AWS Certified Data Engineer - Associate credential, issued by AWS. Passing the exam earns the certification. The acronym is shared by other credentials from other organizations, so it is worth being precise: everything on this page refers only to the AWS data engineering exam. If you want shorter explainers on the naming, see What Does DEA-C01 Stand For? and DEA-C01 Meaning.
The credential validates knowledge of how to build and operate data pipelines on AWS: ingesting data from streaming and batch sources, transforming it, choosing the right stores, cataloging it, keeping pipelines running, and securing and governing the result. It is a knowledge exam delivered as multiple-choice and multiple-response questions. It is not a hands-on lab, and a passing result should not be read as proof of practical competence on its own.
The current exam guide is DEA-C01 Exam Guide v1.1, published December 12, 2025, which is the latest revision listed in AWS's revision record. For a deeper walkthrough of how that guide is organized, read the DEA-C01 exam domains guide.
Exam Format, Fee and Scoring at a Glance
| Item | DEA-C01 detail |
|---|---|
| Issuer | AWS |
| Delivery | Pearson VUE, at a test center or through online proctoring |
| Questions | 65 total: 50 scored, 15 unscored (unscored items are not identified) |
| Time allowed | 130 minutes |
| Question types | Multiple-choice and multiple-response |
| Passing score | Minimum scaled score of 720 on a 100-1,000 scale |
| Fee | USD 150, plus applicable taxes |
| Languages listed | English, Japanese, Korean, Simplified Chinese |
| Validity | Three years |
Because 15 of the 65 questions are unscored and unlabeled, you cannot tell which ones to treat casually. Treat every question as if it counts. For the full cost picture, including how the 50% discount benefit from an active AWS Certification can apply to a next exam (it is a benefit with conditions, not a guaranteed price), see the DEA-C01 certification cost breakdown.
The Four Content Domains and What They Test
The exam objectives are divided into four weighted domains containing 17 tasks in total. The guide itself notes that its lists are not exhaustive, so treat the topics below as a map, not a boundary.
Domain 1: Data Ingestion and Transformation (34%)
The largest domain covers getting data in, reshaping it, orchestrating it, and writing the code and infrastructure that run it.
- Ingestion: streaming reads from Kinesis, Amazon MSK, DynamoDB Streams and DMS; batch reads from S3, Glue, EMR, Redshift, Lambda and AppFlow; schedulers and event triggers using EventBridge and S3 Event Notifications.
- Resilience concepts: throttling and rate limits, stream fan-in and fan-out, replayability of ingestion pipelines, and stateful versus stateless transactions.
- Transformation: Glue, EMR, Lambda and Redshift transformations, converting CSV to Apache Parquet, JDBC and ODBC connections, cost optimization, and integrating LLMs into processing.
- Orchestration: Step Functions, MWAA, Glue workflows, EventBridge and Lambda, with SNS and SQS for notifications.
- Programming concepts: Lambda concurrency, infrastructure as code with CloudFormation and CDK, SAM for serverless pipelines, CI/CD, version control and testing.
Domain 2: Data Store Management (26%)
This domain is about choosing, cataloging, governing the lifecycle of, and modeling data.
- Choosing a store: matching Redshift, DynamoDB, RDS, EMR, Lake Formation, Kinesis Data Streams and MSK to access patterns, cost and performance; Redshift federated queries, materialized views and Spectrum; Apache Iceberg as an open table format.
- Vector concepts: HNSW indexing in Aurora PostgreSQL, IVF as a vector index type, and MemoryDB for fast key/value access.
- Cataloging: the Glue Data Catalog, Hive metastore, Glue crawlers, partition synchronization, and business catalogs with SageMaker Catalog.
- Lifecycle: S3 Lifecycle tiering and expiration, S3 versioning, DynamoDB TTL, and loading and unloading between S3 and Redshift.
- Modeling: schema design, schema evolution, schema conversion, lineage tracking, partitioning, indexing and compression.
Domain 3: Data Operations and Support (22%)
Once pipelines exist, this domain asks how you automate, analyze, monitor and trust them.
- Automation: MWAA, Step Functions, Lambda, EventBridge, SDK access and Athena queries.
- Analysis: Athena, Redshift SQL and views, Athena Spark notebooks, DataBrew, and visualization with QuickSight.
- Monitoring: CloudWatch Logs, CloudTrail, alerts, and log analysis with Athena, OpenSearch Service and CloudWatch Logs Insights.
- Data quality: quality rules and consistency checks in DataBrew, sampling techniques, and handling data skew.
Domain 4: Data Security and Governance (18%)
The smallest domain still matters because it touches every pipeline you design.
- Authentication: VPC security groups, IAM roles, Secrets Manager credential rotation, S3 Access Points and PrivateLink.
- Authorization: custom least-privilege IAM policies, Lake Formation permissions, and role-, tag- and attribute-based approaches.
- Encryption and masking: KMS, cross-account encryption, encryption in transit, and masking or anonymization.
- Audit and privacy: CloudTrail, CloudTrail Lake, PII identification with Macie, AWS Config, preventing data from landing in prohibited Regions, and data sovereignty.
For a single-page revision aid built around these topics, the DEA-C01 cheat sheet condenses the most testable facts.
How the Questions Are Written
The guide describes two item types. A multiple-choice item has one correct answer and three distractors. A multiple-response item has two or more correct responses among five or more options. Because there are no scheduled breaks and one shared 130-minute clock, you have roughly two minutes per question on average, which favors candidates who can recognize patterns quickly.
Typical scenario prompts describe a workload and ask for the best-fit service or configuration. Examples of the kind of reasoning involved include choosing between a streaming service and a batch tool given latency needs, deciding how to partition and compress data for Athena, picking a way to catch schema changes, or selecting the right permission mechanism for column-level access. Distractors are usually plausible services that fit the wrong constraint, such as cost, latency, operational overhead, or governance requirements.
Who Should Sit the Exam
AWS describes the target candidate as someone with two to three years of experience in data engineering or data architecture and one to two years of hands-on AWS experience. This is a recommendation, not a requirement. The guide also describes background knowledge that helps: experience setting up and maintaining ETL pipelines, applying programming concepts independent of a specific language, using Git and source control, understanding data lakes, and a working grasp of networking, storage and compute.
The scope also draws clear lines. Machine learning model training and inference, language-specific syntax, and drawing business conclusions from data are explicitly outside the intended job tasks. Languages such as Python, SQL, Scala and Bash are named, but the exam tests how you apply engineering concepts, not syntax trivia. Likewise, LLM integration, vector indexes and Bedrock knowledge-base concepts appear only as data engineering topics, not as model-building ones. If you are wondering how demanding the exam is for someone at your level, How Hard Is the DEA-C01 Exam? covers difficulty in more depth.
Eligibility, Booking and Test-Day Rules
AWS sets no required prior certification, degree, mandatory course or minimum work-hour total for this exam. The general minimum candidate age is 13, and candidates aged 13 to 17 need parent or guardian consent under AWS policy. A complete walkthrough is available in DEA-C01 requirements.
- Booking: You schedule through Pearson VUE and choose either a test center or online proctoring. Scheduling windows and deadlines are covered in DEA-C01 exam dates.
- Accommodations: An eligible ESL +30-minute accommodation must be requested before you book. It is not added silently to the standard timer.
- Breaks: There are no scheduled breaks. At a test center, unscheduled breaks consume exam time. Online candidates cannot leave camera view for an unapproved break.
- Languages: English, Japanese, Korean and Simplified Chinese are listed.
AWS testing policies govern the finer points of identification, environment and conduct, so check them before exam day rather than relying on assumptions from other vendors.
Scope Details That Trip Up Candidates
A few features of the published scope deserve attention because they are easy to misread or over-generalize.
- The service lists are non-exhaustive and subject to change. The in-scope list spans analytics (Athena, EMR, Glue, DataBrew, Lake Formation, Kinesis, Managed Service for Apache Flink, MSK, OpenSearch Service), application integration, databases, developer tools, migration and transfer, security and storage services. Services such as AWS Elastic Beanstalk, AWS X-Ray, IoT services and media services appear on the out-of-scope list.
- AWS SCT versus DMS Schema Conversion. The v1.1 revision record removes AWS Schema Conversion Tool from the in-scope service list, yet Skill 2.4.3 still names AWS SCT alongside DMS Schema Conversion. These two published observations conflict. Understand the concept of schema conversion and DMS Schema Conversion well, and do not assume the conflict has been resolved either way.
- Quick versus QuickSight. The service inventory says Amazon Quick, while skills 3.2.1 and 3.2.2 say QuickSight. Both labels are published, so recognize both names rather than assuming a particular rename.
- Experience is guidance. Some third-party guides treat recommended experience as mandatory. It is not an AWS admission rule.
Key Takeaway
Study the objectives and task statements in the official guide first, then use the service lists as a cross-check. When the sources disagree, as with SCT, rely on the underlying concept rather than memorizing a single product name.
Careers, Hiring and Career Value
The certification maps to roles that build and maintain data platforms: data engineer, analytics engineer, ETL or pipeline developer, cloud data architect, and data platform engineer. Employers that run data on AWS, from analytics-heavy product companies to consultancies and managed-service providers, tend to value the credential as a signal that you know the AWS service landscape and its trade-offs. Browse the DEA-C01 jobs overview for role types.
On compensation, no verified credential-specific salary premium or issuer pass rate was found in the retrieved sources, so treat any headline figure with caution. The DEA-C01 salary guide and the DEA-C01 ROI analysis evaluate the evidence, and the DEA-C01 pass rate page explains why AWS does not publish a cohort figure.
Validity and Renewal
The certification is valid for three years. There are two verified renewal routes: passing the latest version of the DEA-C01 exam, or passing the AWS Certified Generative AI Developer - Professional exam, which AWS's recertification table also accepts for an active Data Engineer Associate certification. In either case the new three-year period runs from the date you complete the recertification action, not from the previous expiry date. The Data Engineer Associate row lists no CEU or CPE quota and no Skill Builder maintenance route, so do not assume options available to other certifications apply here.
Sequencing Your Preparation Around the Weights
You can build a plan directly from the domain weights. Because Data Ingestion and Transformation is 34% of scored content, it deserves the most time and should come first, since later domains reuse its services. Here is one DEA-C01-specific ordering; adjust the length to your own background. A fuller plan is in the DEA-C01 study guide.
Domain 1: ingestion and transformation
- Compare Kinesis, MSK and DynamoDB Streams, and practice batch versus streaming trade-offs.
- Work through Glue ETL, format conversion to Parquet, and replayability.
- Learn Step Functions, MWAA and EventBridge orchestration patterns.
Domain 2: data stores and catalogs
- Map access patterns to Redshift, DynamoDB, RDS and Lake Formation.
- Cover the Glue Data Catalog, crawlers, partitions, Iceberg and S3 Lifecycle.
Domain 3: operations
- Practice Athena queries, CloudWatch and CloudTrail monitoring, and DataBrew quality rules.
Domain 4: security and governance, then review
- Cover IAM least privilege, KMS, Secrets Manager, Lake Formation permissions and Macie.
- Finish with timed mixed-domain practice and review of weak areas.
Whatever pace you choose, practice under a 130-minute clock before booking, and review why each wrong option fails. Keep in mind that practice scores are only a rough readiness signal because they do not convert to the official scaled score. To drill in the exam's scenario style, try the DEA-C01 practice tests, and for structured courses see DEA-C01 training. Only reputable preparation material written independently of real exam content is worth using.
Frequently Asked Questions
DEA-C01 is the exam code for the AWS Certified Data Engineer - Associate certification. Passing the exam earns the credential, which validates knowledge of building, operating, securing and governing data pipelines on AWS. See also What Is DEA-C01?
There are 65 questions in 130 minutes. Fifty are scored and 15 are unscored, and you cannot tell which are which. Both multiple-choice and multiple-response formats appear.
No. AWS requires no prior certification, degree or mandatory course. The two-to-three years of data engineering and one-to-two years of AWS experience is recommended guidance, not a requirement.
A minimum scaled score of 720 on a 100-1,000 scale. This is not the same as 72% of questions correct, and scoring is compensatory across the whole exam rather than requiring a pass in each domain.
It is valid for three years. You can renew by passing the latest version of the DEA-C01 exam or by passing the AWS Certified Generative AI Developer - Professional exam, and the new period starts when you complete that action.