The AWS Certified Data Engineer – Associate (DEA-C01) is a 65-question, 130-minute exam covering data ingestion, storage, operations, and security on AWS. It costs $150 USD, requires a 720/1000 to pass, and is valid for 3 years. With 2–3 months of focused study, most working data engineers can pass on the first attempt.
- Understand the DEA-C01 exam format, domains, and passing score
- Evaluate whether the AWS data engineer certification is worth it for your career stage
- Follow a structured 4–8 week study plan with the best resources
- Compare AWS DEA-C01 vs Microsoft Fabric DP-700 vs Databricks DE Associate
- Add the certification to your resume and LinkedIn profile effectively
Quick Answers
Is the AWS data engineer certification worth it?
Yes for most data engineers. AWS certifications are requested in job postings more than any other cloud vendor credential, and the DEA-C01 specifically validates the services (Glue, Redshift, Kinesis, S3) that dominate the data engineering job market.
How hard is the AWS Certified Data Engineer Associate exam?
Moderate difficulty. The exam assumes 2–3 years of data engineering experience and 1–2 years of hands-on AWS. If you work with AWS data services daily, expect 4–8 weeks of study. Career changers may need 8–12 weeks.
What is the passing score for DEA-C01?
720 out of 1,000 on a scaled scoring model. The exam has 65 questions (50 scored, 15 unscored pilot questions) and you have 130 minutes.
How long is the AWS data engineer certification valid?
3 years. You recertify by passing the latest version of the exam. If you hold any active AWS certification, you get a 50% discount on the next exam.
The AWS Certified Data Engineer – Associate is the first AWS certification built specifically for data engineers. Launched in 2023, it fills a gap that existed for years — before DEA-C01, data engineers had to cobble together relevance from the Solutions Architect or Data Analytics Specialty exams. Now there is a single credential that maps directly to the data engineering role: pipelines, storage, operations, and governance on AWS.
This guide covers everything from whether the certification is worth your time to a week-by-week study plan — all based on the official AWS exam guide, AWS Skill Builder resources, and practitioner experience.
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Learn how Careery can help youWhat Is the AWS Certified Data Engineer Associate (DEA-C01)?
- AWS Certified Data Engineer – Associate (DEA-C01)
An AWS associate-level certification that validates a candidate's ability to implement data pipelines, monitor and troubleshoot them, and optimize cost and performance — all using AWS services. The exam code is DEA-C01.
The certification tests four core areas of data engineering on AWS:
- Data Ingestion and Transformation — building ETL/ELT pipelines with services like AWS Glue, Kinesis, and Lambda
- Data Store Management — choosing and managing storage (S3, Redshift, DynamoDB, RDS)
- Data Operations and Support — monitoring pipelines, ensuring data quality, operationalizing workflows
- Data Security and Governance — IAM, KMS, Lake Formation, encryption, and logging
DEA-C01 is the only AWS certification designed specifically for data engineers. It covers the exact services — Glue, Redshift, Kinesis, S3, Lake Formation — that appear in most data engineering job postings.
Is the AWS Data Engineer Certification Worth It in 2026?
The short answer: yes, for most data engineers — but the ROI depends on where you are in your career.
When the Certification Helps Most
- Career changers and junior engineers (0–2 years): The certification signals baseline competence to hiring managers who can't evaluate your pipeline experience from a resume alone. It is especially valuable when competing against candidates with CS degrees or data engineering bootcamp certificates.
- Mid-level engineers (2–5 years) looking to move to AWS-heavy shops: If your experience is on Azure or GCP, the DEA-C01 proves you can translate your skills to the AWS ecosystem.
- Consultants and contractors: Clients hiring data engineers for AWS projects often require or strongly prefer AWS certification. Some consulting firms won't staff uncertified engineers on AWS engagements.
When Experience Matters More
- Senior engineers (5+ years) already working on AWS daily: A senior DE with Glue, Redshift, and Kinesis on their resume doesn't need a certificate to prove they know those services. The study time may be better spent on a hands-on project.
- Engineers at companies that don't use AWS: If your employer is all-in on Azure or GCP, the AWS cert adds credential breadth but limited immediate job utility.
For the full picture of how certification affects data engineer compensation — including experience-level breakdowns and location adjustments — see our Data Engineer Salary Guide.
Certification has the highest ROI for career changers, junior engineers, and anyone switching cloud ecosystems. For senior engineers already deep in AWS, the value is more about credential maintenance than career transformation.
Exam Overview: Format, Scoring, and Prerequisites
Format
Scoring
The exam uses compensatory scoring — you do not need to pass each domain individually. A strong performance in one domain can offset a weaker one. The 15 unscored pilot questions are mixed in and not identified, so treat every question as if it counts.
Prerequisites
AWS recommends:
- 2–3 years of data engineering or data architecture experience
- 1–2 years of hands-on experience with AWS services
- Familiarity with ETL pipelines, data lakes, SQL, and basic programming concepts
- Understanding of Git, networking, and compute fundamentals
There is no mandatory prerequisite exam — you can take DEA-C01 without holding any prior AWS certification.
If you hold any active AWS certification, you automatically receive a 50% discount on your next exam ($75 instead of $150). Check your AWS Certification Account for the voucher.
65 questions, 130 minutes, 720 to pass. No prerequisite exams required. The compensatory scoring model means you can afford to be weaker in one domain if you're strong in another.
What's on the Exam: Domain Deep-Dive
Domain 1: Data Ingestion and Transformation (34%)
The largest domain — over a third of scored questions. Covers:
- Setting up data pipelines using AWS Glue, Kinesis Data Streams, Kinesis Data Firehose, and Amazon MSK
- Transforming data with Glue ETL jobs (PySpark, Spark SQL), Glue DataBrew, and Lambda
- Orchestrating workflows with Step Functions, MWAA (managed Airflow), and EventBridge
- Handling batch vs. streaming ingestion patterns
- Schema evolution and data format considerations (Parquet, Avro, JSON, CSV)
Spend the most time here. Know the difference between Glue ETL vs. DataBrew vs. Athena for transformation. Understand when to use Kinesis Data Streams vs. Firehose vs. MSK.
Domain 2: Data Store Management (26%)
- Choosing the right storage: S3 (data lake), Redshift (warehouse), DynamoDB (NoSQL), RDS/Aurora (relational), OpenSearch (search/analytics)
- Data modeling: star schema, denormalization, partition keys for DynamoDB
- Managing data lifecycles with S3 lifecycle policies, Glacier tiering, and Redshift Spectrum
- Lake Formation for centralized permissions and data catalogs
- Cost optimization (S3 storage classes, Redshift reserved nodes, on-demand vs. provisioned DynamoDB)
Domain 3: Data Operations and Support (22%)
- Monitoring with CloudWatch, CloudWatch Logs, and Managed Grafana
- Automating deployments with CloudFormation, CDK, CodePipeline, CodeBuild, CodeDeploy
- Data quality validation and pipeline health checks
- Troubleshooting failed Glue jobs, Redshift query performance, and Kinesis throughput issues
- Cost monitoring with AWS Budgets and Cost Explorer
Domain 4: Data Security and Governance (18%)
- IAM policies, roles, and cross-account access for data pipelines
- Encryption at rest (KMS, S3 SSE) and in transit (TLS)
- Lake Formation fine-grained access control (column-level, row-level)
- Macie for PII detection in S3
- CloudTrail audit logging and compliance
- VPC networking for data services (PrivateLink, VPC endpoints)
Domain 4 is only 18% of the exam, but security questions tend to be the trickiest. Know Lake Formation permissions, KMS key policies, and cross-account IAM patterns cold.
Domain 1 (ingestion/transformation) at 34% is where most points live. Domain 4 (security) at 18% has the fewest questions but the highest "gotcha" potential. Study all four, but allocate time proportionally.
How to Study: 4–8 Week Plan
This plan assumes you're a working data engineer with some AWS experience. Adjust timelines based on your starting point — career changers or those new to AWS may need 8–12 weeks.
Weeks 1–2: Foundations and Domain Mapping
Goal: Understand the exam scope and fill knowledge gaps.
- Read the official AWS exam guide end-to-end. Map each domain to services you know vs. services you don't.
- Take the AWS Certification Official Practice Question Set (free on Skill Builder) to establish a baseline score. Don't worry about the result — use it to identify weak areas.
- Review AWS documentation for unfamiliar services. Focus on Glue, Lake Formation, and Kinesis if they're new to you.
- Complete the Exam Prep Standard Course on AWS Skill Builder (free tier).
Weeks 3–4: Hands-On Labs
Goal: Build muscle memory with the core services.
- Use AWS Free Tier or a sandbox account to complete labs:
- Build an S3 → Glue ETL → Redshift pipeline
- Set up a Kinesis Data Stream with a Lambda consumer
- Configure Lake Formation permissions on an S3-based data lake
- Create a Step Functions workflow that orchestrates Glue jobs
- Complete AWS Builder Labs (Skill Builder subscription) or equivalent free tutorials.
- Study the in-scope AWS services list — know what each service does at a high level.
Weeks 5–6: Practice Exams and Weak Area Review
Goal: Simulate exam conditions and close remaining gaps.
- Take the AWS Certification Official Pretest (Skill Builder) — this is closer to real exam difficulty than the practice question set.
- Take 2–3 full-length practice exams from a reputable provider (Tutorials Dojo, Whizlabs, or Skill Builder subscription).
- For every wrong answer, read the AWS documentation for that service. Don't just memorize the answer — understand why one option is better.
- Create flashcards for service comparisons (e.g., "When to use Kinesis vs. MSK" or "Glue ETL vs. DataBrew vs. Athena").
Weeks 7–8: Final Review and Exam Scheduling
Goal: Consolidate knowledge and take the exam with confidence.
- Retake the official practice question set. Target 85%+ before scheduling.
- Review the exam guide's domain descriptions one more time. Make sure you can explain each task statement in your own words.
- Schedule the exam at least 1 week in advance — popular time slots fill up.
- The night before: review your flashcards, get 8 hours of sleep. No cramming.
I'm preparing for the AWS Certified Data Engineer Associate (DEA-C01) exam. My background: - Current role: [YOUR ROLE] - Years of data engineering experience: [X] - AWS services I use daily: [LIST SERVICES] - AWS services I've never used: [LIST SERVICES] - Hours per week I can study: [X] - Target exam date: [DATE] Based on the DEA-C01 exam domains: - Domain 1: Data Ingestion and Transformation (34%) - Domain 2: Data Store Management (26%) - Domain 3: Data Operations and Support (22%) - Domain 4: Data Security and Governance (18%) Create a week-by-week study schedule that: 1. Prioritizes domains proportionally to their exam weight 2. Front-loads my weakest areas 3. Includes specific AWS Skill Builder courses and hands-on labs 4. Reserves the final week for practice exams only
The most common mistake is spending too much time on theory and not enough on hands-on labs. The exam tests practical decision-making — "which service would you use for this scenario?" — not memorized definitions.
Best Study Resources (Ranked)
Free Resources
Paid Resources
For a detailed roadmap on building data engineering skills — including which certifications matter at each career stage — see the practitioner guide from a data engineer at Optum: Data Engineer Roadmap: Complete Guide.
Common Study Mistakes
- Studying only theory without hands-on labs — the exam tests practical decision-making, not definitions
- Ignoring Domain 4 (Security & Governance) because it's the smallest — security questions are often the trickiest
- Using brain dumps or leaked questions — AWS rotates questions frequently, and dumps often contain wrong answers
- Spending weeks on services outside the exam scope — check the official in-scope services list before deep-diving
- Not taking practice exams under timed conditions — 130 minutes for 65 questions is roughly 2 minutes per question
How to Register and Schedule the Exam
Create an AWS Training Account
Go to aws.training and sign in with your Amazon account (or create one). This is your central hub for all AWS certifications.
Open Your AWS Certification Account
From the AWS Training dashboard, click Certification in the top navigation, then AWS Certification Account. This opens the Pearson VUE scheduling portal linked to your AWS profile.
Schedule the Exam
Click Schedule New Exam → find AWS Certified Data Engineer – Associate (DEA-C01) → click Schedule with Pearson VUE. Choose between:
- Test center — select a location near you and pick a date/time
- Online proctored (OnVUE) — available 24/7 in English. You'll need a webcam, microphone, and a clean desk.
Apply Your Discount (If Eligible)
If you hold any active AWS certification, a 50% discount voucher ($75 off) appears automatically in your Certification Account. Apply it during checkout.
Prepare Your ID
You need a government-issued photo ID (passport, driver's license) that matches the name on your AWS Certification Account exactly. For online proctored exams, also run the Pearson VUE system check to verify your computer meets the requirements.
- Schedule exam: aws.training/certification
- Pearson VUE AWS page: pearsonvue.com/aws
- Online testing requirements: Pearson VUE OnVUE
- Exam policies & ID requirements: aws.amazon.com/certification/policies
AWS DEA-C01 vs Microsoft Fabric DP-700 vs Databricks — Which Should You Get?
Choosing between cloud data engineering certifications depends on your current tech stack and career goals. Here is how the three major options compare:
Which One First?
- If most job postings you're targeting mention AWS: Start with DEA-C01. AWS leads the cloud market in data engineering tooling, and more job descriptions reference AWS services than any other cloud.
- If your company uses Microsoft Fabric: Get DP-700. Note that the older Azure DP-203 was retired in March 2025 and replaced by DP-700, which focuses on Microsoft Fabric instead of legacy Azure Data Factory. See our Azure Data Engineer Certification (DP-700) Guide for the full study plan.
- If you work with Databricks daily: The Databricks DE Associate validates your Spark and Delta Lake skills. It pairs well with a cloud cert (AWS or Azure) since Databricks runs on top of those clouds. See our Databricks Data Engineer Certification Guide for the full study plan.
- Best two-cert combo: AWS DEA-C01 + Databricks DE Associate covers the broadest set of job requirements.
For a broader comparison of all data engineering certifications — including Google Cloud Professional Data Engineer and dbt — see our guide: Best Data Engineering Certifications.
AWS DEA-C01 has the widest market applicability. Microsoft DP-700 is the right choice for Fabric shops. Databricks DE Associate complements either cloud cert. Get the one that matches the jobs you're applying to.
How to Add This Certification to Your Resume and LinkedIn
Earning the certification is step one. Making it visible to recruiters and hiring managers is step two.
Resume
- Certifications section: List as "AWS Certified Data Engineer – Associate (DEA-C01)" with the year earned.
- Don't bury it. Place the certifications section right after Technical Skills — before experience for junior engineers, after experience for senior engineers.
- ATS keywords: Include both "AWS Certified Data Engineer" and "DEA-C01" so ATS filters catch it regardless of how the recruiter configures the search.
- Add via LinkedIn's certification feature: Go to Profile → Add section → Licenses & Certifications. Use the official name: "AWS Certified Data Engineer – Associate." Link to the AWS validation page.
- Headline update: Add the credential abbreviation to your headline. Example: "Data Engineer | AWS DEA-C01 | Python, Spark, Redshift."
- Post about it. A short post about passing the exam and what you learned gets 3–5x the engagement of a silent profile update.
For the complete guide on structuring your data engineer resume — including the bullet formula, ATS keywords, and experience templates by seniority level — see our Data Engineer Resume Guide.
List the certification with its full name and exam code on your resume. On LinkedIn, add it via the Certifications feature and update your headline. Both steps take 5 minutes and dramatically increase recruiter visibility.
Exam Day Checklist
- Government-issued photo ID ready (must match your AWS Certification account name exactly)
- If online proctored: clean desk, close all apps, stable internet, webcam and mic working
- If test center: arrive 15 minutes early, know the address and parking situation
- Read and accept the NDA — don't skip it, or you'll lose time re-reading
- Scratch paper / whiteboard provided (test center) or virtual notepad (online) — use it for service comparison notes
- Flag difficult questions and come back — don't spend more than 3 minutes on any single question
- Read every option fully before selecting — AWS loves "most correct" answers where two options seem right
- Eliminate obviously wrong answers first — even guessing between two is a 50% chance
- Watch for "least cost" and "most operationally efficient" qualifiers — they change the correct answer
- Use all 130 minutes — review flagged questions with remaining time
Key Takeaways
- 1The AWS DEA-C01 is a 65-question, 130-minute exam costing $150 USD with a 720/1000 passing score — valid for 3 years.
- 2Domain 1 (Data Ingestion & Transformation) is 34% of the exam — allocate your study time accordingly.
- 3The certification has the highest ROI for junior engineers, career changers, and anyone transitioning to AWS from another cloud.
- 4Use the official AWS Skill Builder resources as your primary study material — they're free, current, and aligned to the exam.
- 5Hands-on labs matter more than video courses. Build real pipelines with Glue, Kinesis, and Redshift on the AWS Free Tier.
- 6AWS DEA-C01 has the broadest market applicability. Pair it with Databricks DE Associate for maximum coverage.
Frequently Asked Questions
Can I take the AWS Data Engineer Associate exam with no AWS experience?
Technically yes — there are no prerequisite exams or mandatory experience requirements. However, AWS recommends 1–2 years of hands-on AWS experience and 2–3 years of data engineering background. Without real-world AWS exposure, expect to invest 8–12 weeks of study with heavy lab work.
Is the DEA-C01 exam harder than AWS Solutions Architect Associate?
They're comparable in difficulty but different in focus. Solutions Architect (SAA-C03) is broader across all AWS services; DEA-C01 is narrower but deeper in data services specifically. If you already work with Glue, Redshift, and Kinesis, DEA-C01 may feel easier because the questions map to your daily work.
Should I get AWS DEA-C01 or the Databricks Data Engineer Associate first?
Get the one that matches the tech stack in your target job postings. If most roles mention AWS services (Glue, Redshift, S3), start with DEA-C01. If they mention Databricks or Delta Lake, start with Databricks. For maximum coverage, plan to get both within 6 months.
How often does AWS update the DEA-C01 exam?
AWS periodically revises exam content to reflect new services and features. Revisions are published at least one month before changes appear on the exam. Check the exam guide's Revisions section for the latest updates.
What happens if I fail the exam?
You can retake the exam after a 14-day waiting period. There is no limit on the number of attempts, but each retake costs the full $150 USD (or $75 if you have the 50% discount from a prior certification). Many candidates who fail are within 20–50 points of passing — a focused review of weak domains and 1–2 more practice exams usually closes the gap.
Do I need to know Python or SQL for the exam?
You need to understand programming concepts at a high level, but the exam does not test language-specific syntax. You won't write code during the exam. Knowing how Glue uses PySpark and how Athena and Redshift use SQL is more important than memorizing syntax.
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Sources & References
- AWS Certified Data Engineer – Associate (DEA-C01) Exam Guide — Amazon Web Services (2025)
- AWS Certified Data Engineer – Associate Certification Page — Amazon Web Services (2025)
- In-Scope AWS Services for DEA-C01 — Amazon Web Services (2025)
- AWS Skill Builder: Data Engineer Associate Exam Prep — Amazon Web Services (2025)
- Designing Data-Intensive Applications — Martin Kleppmann (2017)