Study guide · Exam overview
The format, passing score, and four content domains of the AWS Certified Data Engineer – Associate exam, plus the pipeline choices worth practicing before you book DEA-C01.
Exam version notice: This overview follows the AWS Certified Data Engineer – Associate Exam Guide (DEA-C01), version 1.1, published December 12, 2025. The guide lists four domains, 50 scored questions plus 15 unscored questions, and a scaled passing score of 720. Pricing, languages, and delivery options can change. Confirm them on the AWS certification site before you register. Items tagged Extra are useful context that the exam guide places out of scope, or services version 1.1 removed from the in-scope list. If core service names are still new, start with the Cloud Practitioner overview.
DEA-C01 checks whether you can build and run a data pipeline on AWS. The exam guide says the target candidate has the equivalent of 2 to 3 years in data engineering and at least 1 to 2 years of hands-on AWS experience. The work is to ingest data, transform it, land it in a store that matches the access pattern, keep the pipeline observable, and restrict who can read it.
A question usually gives a constraint: a stream that must be replayed, a nightly file that must become columnar, a catalog that analysts already query, a quality rule, or a Region the data must stay inside. Two options often both “work.” The better answer is the one that meets the constraint with the least extra moving parts. Read the noun the stem cares about: how the data arrives, where it must be queryable, what failed, or who is allowed to see a column.
The exam guide also names work the target candidate is not expected to do: train or run machine learning models, recite language-specific syntax, or draw business conclusions from the data. A question that seems to ask for a model-training step is usually asking for a pipeline step instead. Version 1.1 added skills for large language models in data processing, Apache Iceberg, vector index types, and Amazon SageMaker Catalog. Those are in scope. Training a model is still listed as out of scope.
Figures below come from the DEA-C01 exam guide, version 1.1, and the AWS certification page reviewed in October 2026.
| Specification | DEA-C01 |
|---|---|
| Level | Associate. There is no required prerequisite certification. |
| Number of questions | 65. Fifty affect your score. Fifteen are unscored and are not identified on the exam. |
| Question types | Multiple choice (one correct answer and three distractors) and multiple response (two or more correct answers out of five or more options). |
| Length of test | 130 minutes. AWS offers an additional 30 minutes for eligible non-native English speakers who request the ESL accommodation before they register. |
| Passing score | 720 on a scaled range of 100–1,000. Scoring is compensatory: you pass the exam as a whole, not each domain. |
| Recommended experience | 2 to 3 years of data engineering, including at least 1 to 2 years of hands-on work with AWS services. |
| Exam price | Associate exams are listed at 150 USD. Taxes and local-currency prices can differ. Confirm the current fee before you book. |
| Validity | Three years. Confirm the current recertification options with AWS. |
Unanswered questions are scored as incorrect. There is no penalty for guessing, so answer every question. A scaled score of 720 is not the same thing as 72 percent of the questions. The exam uses official short names, and the in-exam Help lists the matching full service names.
These percentages are the share of scored content in the official exam guide. The 200 practice questions on this site follow the same weights.
The largest domain. Get data in, change its shape, and run the workflow.
Pick the store, catalog the schema, and let the data age on purpose.
Keep the pipeline running and the data trustworthy.
Who can read a column, how it is encrypted, and which Region it may enter.
The exam guide publishes an in-scope list and an out-of-scope list. Learn the in-scope services first. The same map is in the core notes and flashcards.
| Pipeline need | Prefer | Remember |
|---|---|---|
| A stream consumers can replay | Amazon Kinesis Data Streams or Amazon MSK | Kinesis Data Firehose delivers to a destination. It is not the replay log. |
| Load a stream into S3 with little code | Amazon Kinesis Data Firehose | Firehose can buffer and convert formats. You do not manage shards for that path. |
| A nightly Spark transform | AWS Glue or Amazon EMR | Glue fits a managed job. EMR fits a cluster you tune, including Spot task nodes. |
| SaaS records into S3 | Amazon AppFlow | AppFlow is for supported SaaS applications. It is not a Kafka cluster. |
| Database change capture into AWS | AWS DMS | DMS moves and replicates databases. A multi-stage Spark job is Glue or EMR. |
| SQL on files in S3, used occasionally | Amazon Athena | You pay for data scanned. Partition and use a columnar format before you scale the warehouse. |
| Concurrent SQL analytics on a warehouse | Amazon Redshift | Spectrum reads S3. A federated query reads a remote database. COPY loads data into the warehouse. |
| Key lookup at high request rates | Amazon DynamoDB | TTL expires items. DynamoDB Streams publishes item changes. Ad hoc SQL belongs elsewhere. |
| Shared table metadata | AWS Glue Data Catalog | A crawler infers schemas. SageMaker Catalog is the business catalog in exam guide 1.1. |
| Schema evolution on the data lake | Apache Iceberg, including Amazon S3 Tables | Iceberg is the open table format named in the guide. S3 Tables was added to the in-scope list in version 1.1. |
| Column-level lake permissions | AWS Lake Formation | Lake Formation grants access to cataloged data. It is not the bucket that stores the files. |
| Find sensitive data in S3 | Amazon Macie | Macie classifies objects. AWS WAF inspects HTTP. It does not scan a data lake. |
| Rotate a database password | AWS Secrets Manager | Parameter Store can hold a value. The exam guide points credential rotation at Secrets Manager. |
| Extra A managed data-science environment | Amazon FinSpace | Listed as out of scope. Use the in-scope analytics services for the pipeline. |
| Extra Schema conversion with AWS SCT | AWS DMS Schema Conversion | Version 1.1 removed AWS SCT from the in-scope service list. The schema-conversion skill still names DMS Schema Conversion. |
| Extra Train a custom model | Leave it out of the pipeline answer | The exam guide says model training and inference are out of scope for the target candidate. Calling Amazon Bedrock to extract or classify text in a pipeline is the in-scope skill. |
Multiple choice has one correct response and three distractors. Multiple response has two or more correct responses out of five or more options. The stem tells you how many to choose. Select every response that completes the statement, and nothing extra.
Distractors are real services that solve a nearby problem. If the need is “replay yesterday’s events,” Firehose is the nearby wrong answer because it delivers and moves on. If the need is “scan less data in Athena,” a bigger Redshift cluster is the nearby wrong answer because the files are still in S3. If the need is “hide one column from an analyst,” a bucket policy that blocks the whole prefix is broader than the stem asked for.
Words such as MOST, BEST, and LEAST are the constraint. MOST cost-effective still has to meet the latency or freshness number in the stem. LEAST operational overhead usually means a managed service. There is no published penalty for a wrong guess. A blank answer is incorrect.
A practical sequence once you can already name the core AWS services.
Say whether the data is a file on a schedule, a stream you must replay, a SaaS export, or a database change log. The service follows that sentence.
Key lookup, occasional SQL on S3, or a busy warehouse. Then decide whether the data should be copied in, queried in place, or expired.
Glue Data Catalog for technical schemas, a crawler or partition sync when new folders appear, and a columnar or Iceberg table when the schema will change.
Add the alarm, the log, and the quality check. Skew, empty fields, and a bookmark that skipped a day are the usual failures.
Use the four decks until you can answer before the card flips. Revisit misses the next day.
Work through original questions at about two minutes each, review every explanation, and return to the notes on domains below 75 percent. Aim for a steady 85 percent before you book.
The overview, core notes, flashcards, and practice exams are all published.
Exam format, the 720 passing score, domain weights, and a study plan.
Reference notes for ingestion, stores, operations, and governance.
40 recall cards in four decks, plus memory notes for streams, stores, and access.
200 original questions with custom exams, explanations, and a score report by domain.
The current associate data engineer exam in the AWS exam guide is DEA-C01. This overview follows exam guide version 1.1, published December 12, 2025. Confirm the code on the AWS certification page before you book, because AWS can retire an exam version.
Results use a scaled score from 100 to 1,000. The minimum passing score is 720. You do not need a passing score in every domain. A scaled score is not the percentage of questions you answered correctly.
The exam has 65 questions and a 130-minute time limit. Fifty questions affect your score. Fifteen are unscored and are not labeled. Question types are multiple choice and multiple response.
There is no required prerequisite certification. AWS describes the target candidate as someone with the equivalent of 2 to 3 years of data engineering experience and at least 1 to 2 years of hands-on experience with AWS services.
AWS certifications are valid for three years. Recertification options can change, so confirm the current policy with AWS before your expiration date.
No. The practice questions on this site are original. They are not AWS exam items, and a practice score does not predict a result.
Service names and prices change. Use the current AWS exam guide and the AWS certification site as the authority when they differ from these notes.
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