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AWS · DEA-C01 · Intermediate

AWS Data Engineer - Associate (DEA-C01) — Practice Questions and Mock Exam

Prepare for DEA-C01 with original practice questions and clear answer explanations. Ask Alex, your AI tutor, when you need more detail, use your results to identify topics to review, and practice your pacing with timed mock exams.

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65Mock exam questions

130minTime limit

720/ 1000Passing score

Checked against AWS · August 2026 · Current exam version

Overview

About the exam

The AWS Certified Data Engineer – Associate validates the ability to design and implement data pipelines, manage data stores, and ensure data quality and governance on AWS. It covers data ingestion and transformation using services like Glue and Kinesis, data store management with Redshift and S3, operational support, and data security best practices.

This certification is designed for data engineers with the equivalent of two to three years of experience in data engineering and at least one to two years of hands-on experience with AWS services. It demonstrates proficiency in designing cost-effective, scalable data architectures using AWS-native services.

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Try five DEA-C01 questions

Try five practice questions from the app’s current AWS Certified Data Engineer - Associate question bank, with answers and explanations.

Data Security and Governance1 / 5

A data engineer needs row-level AND column-level security for a data lake table in S3 queried by Athena. Different teams see different subsets of rows and columns. Which service provides BOTH in a centralized way?

AlexFull explanation from Alex

AWS Lake Formation data filters provide column-level, row-level, and cell-level security for Data Catalog tables stored in S3. Each data filter specifies: (1) a column specification to include/exclude columns, and (2) a row filter expression (PartiQL WHERE clause) restricting visible rows. When both are set, you get cell-level security. Permissions are enforced through Athena, Redshift Spectrum, and EMR. IAM policies with S3 prefix conditions operate at the object/prefix level, not row/column level. Glue Data Catalog resource policies control catalog-level access, not data-level filtering. Athena workgroup settings manage query execution and cost, not data security. Ref: docs.aws.amazon.com/lake-formation/latest/dg/data-filtering.html

Sourcedocs.aws.amazon.com

Data Ingestion and Transformation2 / 5

A data engineer needs to orchestrate a multi-step data pipeline that includes an AWS Glue crawler, followed by an AWS Glue ETL job, and then a notification via Amazon SNS upon completion. The pipeline should run daily. Which combination of services provides the MOST operationally efficient solution?

AlexFull explanation from Alex

Use AWS Glue workflows when the dependency graph is made up of Glue crawlers and Glue jobs. A workflow start trigger can be scheduled daily, and conditional triggers can run later Glue steps after earlier steps complete. For notifications, AWS Glue emits EventBridge events for job and crawler state changes. An EventBridge rule can match the desired completion state and notify an Amazon SNS topic. Step Functions is valid for more heterogeneous orchestration, but it is not the lowest-overhead choice for a small Glue-native pipeline plus notification.

Sourcedocs.aws.amazon.com

Data Store Management3 / 5

A data engineer needs to manage the lifecycle of data stored in Amazon S3 to optimize costs. Raw data should remain in S3 Standard for 30 days, then move to S3 Standard-IA for 90 days, and finally transition to S3 Glacier Deep Archive. Which AWS feature should the engineer configure?

AlexFull explanation from Alex

S3 Lifecycle policies automate object transitions between storage classes based on age. Rules define transitions: Standard → Standard-IA (30 days) → Glacier Flexible → Glacier Deep Archive, following the storage class waterfall. Minimum storage durations apply (30 days IA, 90 days Glacier, 180 days Deep Archive). Policies apply to buckets, prefixes, or tags with optional expiration rules. S3 Replication copies objects across buckets/regions but doesn't change storage classes over time. S3 Object Lock prevents deletion/modification for compliance (WORM), not cost optimization. S3 Intelligent-Tiering automatically moves objects between access tiers based on usage patterns but doesn't follow the fixed time-based schedule specified in this scenario. Ref: docs.aws.amazon.com/AmazonS3/latest/userguide/object-lifecycle-mgmt.html

Sourcedocs.aws.amazon.com

Data Operations and Support4 / 5

A data platform team needs to build a centralized observability dashboard that visualizes metrics from multiple AWS data services including AWS Glue, Amazon Redshift, Amazon EMR, and Amazon Kinesis. The dashboard must support custom alerting rules and integrate with PagerDuty for incident notification. Which AWS service provides these capabilities as a fully managed solution?

AlexFull explanation from Alex

Amazon Managed Grafana is a fully managed visualization service natively integrating with AWS data sources including CloudWatch, OpenSearch, X-Ray, Timestream, and Managed Prometheus. It enables centralized observability dashboards combining metrics from Glue, Redshift, EMR, Kinesis, and other services. Grafana supports custom alerting rules with contact points including PagerDuty, Slack, SNS, and email. It handles infrastructure, scaling, patching, and HA, with IAM Identity Center (SSO) for authentication. The option “Amazon CloudWatch Dashboards” (CloudWatch Dashboards) provides basic CloudWatch metric visualization but has limited customization, no native PagerDuty integration, and cannot natively combine non-CloudWatch sources. The option “AWS X-Ray service map” (X-Ray service map) focuses on distributed tracing, not general observability dashboards. The option “Amazon QuickSight” (QuickSight) is a BI service for data analytics and reporting, not operational monitoring or alerting.

Sourcedocs.aws.amazon.com

Data Security and Governance5 / 5

A data governance team manages a data lake with hundreds of databases and thousands of tables in the AWS Glue Data Catalog. They need to implement access control that scales efficiently without creating individual permissions for each table. When new tables are added to a database, they should automatically inherit the correct access permissions based on their data classification (e.g., 'PII', 'confidential', 'public'). Which AWS Lake Formation feature meets this requirement?

AlexFull explanation from Alex

Lake Formation tag-based access control (LF-TBAC) uses LF-Tags—key-value pairs like classification=PII—assigned to Data Catalog resources. Permissions are granted via tag expressions rather than individual resource grants. Tables inherit tags from databases and columns inherit from tables, so new tables automatically inherit permissions without manual grants. For N principals and R resources, named resource grants require N×R operations vs. N+R with LF-TBAC. IAM identity-based policies require per-table resource ARNs that don't scale for thousands of tables. Named resource grants require individual per-table permissions without inheritance. S3 bucket policies operate at the object/prefix level and don't understand table/column structure. Ref: docs.aws.amazon.com/lake-formation/latest/dg/tag-based-access-control.html

Sourcedocs.aws.amazon.com

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Question pool

331 practice questions

The Pass-IT question pool gives you material to practice for DEA-C01. A Pass-IT mock exam uses 65 questions and a 130-minute time limit; these are practice settings.

Pool details: DEA-C01

Passing score720 / 1,000

as published by AWS

Objectives in the guide17 objectives listed in the official guide

across 4 domains in the official exam guide

Pool size331 questions

= The pool size is equivalent to 5 sets of 65 questions; this does not mean that each mock exam uses a separate set.

Blueprint domains4 domains in the exam blueprint

Data Ingestion and Transformation 114 · Data Store Management 88 · Data Operations and Support 73 · Data Security and Governance 56

Recorded as checked against sources331 of 331

questions recorded as having their answer, options, and explanation checked against official AWS documentation

How questions are made →

Exam domains

What's on the exam

Data Ingestion and Transformation carries the most weight at 34%, covering how source data gets pulled in (streaming or batch), reshaped into a usable format, and pushed through an orchestrated workflow, plus the coding discipline and automation habits behind a maintainable pipeline. Data Store Management follows at 26%, testing whether a candidate can match a workload to the right storage service among AWS's relational, NoSQL, and lake-house options, keep that data discoverable through cataloging, retire it on a defined schedule, and adjust its schema as requirements shift.

Data Operations and Support takes 22%, automating pipelines with Glue and Lambda, analyzing data through Athena and QuickSight, and troubleshooting failures once they're in production. Data Security and Governance closes the blueprint at 18%, and it's where IAM, Lake Formation permissions, encryption, and PII handling live — a domain candidates who focus purely on pipeline mechanics tend to shortchange.

Exam blueprint: DEA-C01

Data Ingestion and Transformation34%

Ingest data from streaming and batch sources using services such as Kinesis, Glue, and Lambda, and transform and process data across formats while integrating multiple sources. Also covers orchestrating ETL pipelines with tools like Step Functions and MWAA, and applying programming and infrastructure-as-code practices to data engineering.

≈ 17 h

Data Store Management26%

Pick the right storage service for the workload, weighing options like Amazon Redshift, DynamoDB, and AWS Lake Formation, track it in a data catalog, manage how long it lives through tiering and retention, and design schemas that can evolve as requirements change.

≈ 13 h

Data Operations and Support22%

Automate data processing using AWS services such as Glue, Lambda, and EventBridge, analyze and visualize data with tools like Athena and QuickSight, and maintain, monitor, and troubleshoot data pipelines while ensuring data quality through validation checks.

≈ 11 h

Data Security and Governance18%

Apply authentication and authorization mechanisms such as IAM roles, policies, and Lake Formation permissions to data resources, and implement data encryption and masking to meet compliance requirements. Also covers preparing logs for audit and applying data privacy and governance practices such as PII identification and data sovereignty.

≈ 9 h

Format

Exam format and question types

The exam draws 65 questions (50 scored, 15 unscored) from multiple-choice and multiple-response formats inside a 130-minute window. Most items are scenario-based, describing a pipeline requirement or data architecture problem and asking which combination of Glue, Kinesis, Redshift, Athena, or Lake Formation resolves it. At roughly 2 minutes per question, the pace rewards recognizing the right service family quickly rather than working through every option.

Question types: DEA-C01

Multiple Choice65%

Select the single answer that best meets the question’s requirements.

Multiple Response35%

Select multiple answers. Follow the question’s instructions on how many to choose.

See AWS for official question-format information. The shares shown describe the Pass-IT practice pool; they do not establish the proportions on the official exam.

Planning

Preparing for DEA-C01

The exam runs through Pearson VUE, either at a testing center or online with a remote proctor, and is offered in English, Japanese, Korean, and Simplified Chinese. Certification holds for 3 years; renewal means passing a recertification exam before it expires, or earning a higher-level AWS certification, which renews it automatically.

Preparation and logistics: DEA-C01

Preparation

Illustrative study time30–75 h

illustrative planning range: 30 h with relevant experience to 75 h when starting out; your needs may fall outside this range

LevelIntermediate

Taking and maintaining the certification

DeliveryPearson VUE testing center or online proctored exam

Retake policy14-day waiting period between exam attempts, no limit on total number of attempts

Certification validity3 years

Pass a recertification exam before the 3-year expiration date, or earn a higher-level AWS certification to automatically renew

Official guideView on provider site

Study notes

Common pitfalls

Topics to review: DEA-C01

01Glue vs EMR
Not understanding when to use AWS Glue's serverless ETL versus Amazon EMR's managed Hadoop/Spark clusters for different data processing workloads.
02Lake Formation
Misunderstanding Lake Formation's role in data governance, fine-grained access control, and how it integrates with Glue and Athena.
03Streaming vs Batch
Confusing when to use Kinesis Data Streams, Kinesis Firehose, or batch-based Glue jobs for different data ingestion requirements.
04Storage Tiers
Choosing the wrong S3 storage class or Redshift node type for specific query patterns, data access frequency, and cost constraints.
05Data Quality
Not knowing how to implement data validation, deduplication, and schema evolution strategies using AWS-native data quality tools.

Practice with questions and explanations in Pass-IT →

Questions

Frequently asked questions

How long is the AWS Certified Data Engineer - Associate exam?

The DEA-C01 exam has 65 questions and a 130-minute time limit.

What is the passing score for AWS Certified Data Engineer - Associate?

The passing score for the DEA-C01 exam is 720 / 1000.

Which pitfalls should I review when preparing for AWS Certified Data Engineer - Associate?

Topics to review include Glue vs EMR, Lake Formation, Streaming vs Batch, Storage Tiers, Data Quality. Work through examples to check that you understand the distinctions and can explain your answer.

Which AWS certification fits a data engineer?

DEA-C01 is the one written for the role: ingestion and transformation alone is 34% of it, with data store management at 26%. MLA-C01 is the neighbouring associate exam if your pipelines end in model training, and SAA-C03 is a general architecture exam rather than a data one. Pick DEA-C01 if your day is pipelines, and MLA-C01 if it is features and models.

How is the DEA-C01 exam weighted?

Data ingestion and transformation is the heaviest domain at 34%, followed by data store management at 26% and data operations and support at 22%. Data security and governance takes the remaining 18%. Six questions in ten come from the first two domains, so pipeline and storage work deserves most of the preparation.

How long is DEA-C01 valid?

Three years. You renew either by sitting the recertification exam before the expiry date or by earning a higher-level AWS certification, which renews it for you. AWS offers no continuing-education route.

What happens if you fail DEA-C01?

AWS makes you wait 14 days before the next attempt. There is no cap on how many times you can sit it, so the only hard limit is that two-week gap.

Do you need CLF-C02 before DEA-C01?

No, AWS sets no formal prerequisite for DEA-C01. The catalog budget is around 50 hours and assumes working knowledge of SQL and of AWS storage services. Cloud Practitioner helps if AWS itself is new to you, but it teaches nothing about pipelines.

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