The AWS Certified Data Engineer – Associate (DEA-C01) is a brand-new certification launched by AWS to validate your ability to work with data pipelines, storage solutions, analytics tools, and security best practices on the AWS platform. It is designed to test real-world, hands-on knowledge in building, maintaining, and optimizing data engineering solutions using core AWS services.
This certification is ideal for Data Engineers, Cloud Engineers, Big Data Developers, and Analytics Professionals who are already familiar with the basics of AWS and want to prove their skills in managing data end-to-end – from ingestion to transformation, storage, and access control.
In 2025, as data continues to grow in volume and complexity, companies are investing heavily in cloud-native data infrastructure. AWS remains the market leader in cloud services, and having a certification like DEA-C01 on your resume can be a game-changer. It not only helps you stand out to employers but also demonstrates your ability to design scalable, secure, and cost-effective data workflows.
What is the AWS Certified Data Engineer – Associate (DEA-C01)?
The AWS Certified Data Engineer – Associate (DEA-C01) is a new certification by AWS that validates your ability to design, build, manage, and optimize data pipelines and data workflows using AWS services. It is tailored for professionals working with large-scale datasets in the cloud, especially those involved in extracting, transforming, loading (ETL), and analyzing data.
This certification demonstrates your hands-on expertise with services like AWS Glue, Redshift, Kinesis, S3, IAM, Athena, and others. It focuses on building scalable and secure data systems, both for real-time and batch processing.
Overview of the Certification
The DEA-C01 certification helps data professionals prove their ability to manage the entire lifecycle of data in AWS — from ingestion and storage to analysis and optimization. It bridges the gap between traditional data engineering and modern cloud-native solutions.
Prerequisites
There are no mandatory prerequisites, but it is recommended that candidates have:
- 1–2 years of experience in data engineering or analytics roles
- Working knowledge of AWS services related to data workflows
- Basic understanding of SQL, ETL tools, and cloud security practices
Exam Format
| Feature | Details |
|---|---|
| Exam Code | DEA-C01 |
| Type | Associate-level certification |
| Format | Multiple choice and multiple response |
| Duration | 130 minutes |
| Delivery Method | Pearson VUE or PSI (online or test center) |
| Language | English, Japanese, Korean, Simplified Chinese |
| Cost | $150 USD |
| Result | Pass/Fail (scaled score) |
Official Domains Covered in the Exam
The exam covers five key domains:
1. Data Ingestion and Transformation
This domain focuses on your ability to build data pipelines that collect and process information from various sources. It includes both real-time streaming and batch processing. You are expected to know how to use services like AWS Glue and Amazon Kinesis to transform raw data into structured formats suitable for analysis.
2. Data Storage and Management
In this domain, you’ll need to demonstrate how to choose the right AWS storage solutions—like Amazon S3, Redshift, RDS, or DynamoDB—based on different use cases. You should understand how to manage data organization, access patterns, partitioning strategies, and lifecycle policies that help improve efficiency and reduce costs.
3. Data Analysis and Visualization
This part of the exam tests your ability to analyze data using AWS-native tools like Athena, Redshift Spectrum, and QuickSight. You should be comfortable querying large datasets and designing dashboards that turn data into actionable insights for business users.
4. Data Security and Governance
Here, the focus is on protecting data through encryption, access controls, and compliance best practices. You’ll need to understand how to apply Identity and Access Management (IAM) policies, work with Lake Formation, and ensure that data workflows meet security and regulatory requirements.
5. Monitoring and Optimization
This domain assesses your skills in observing and improving the performance of data systems. You’ll be tested on how well you can use tools like CloudWatch and CloudTrail for monitoring, and how you can troubleshoot pipeline issues, optimize cost, and fine-tune system performance.
Who should take this Certification?
The AWS Certified Data Engineer – Associate (DEA-C01) is designed for professionals who work with data in the cloud and are responsible for building, managing, and optimizing data pipelines. If you regularly handle tasks like data ingestion, transformation, storage, and analysis using AWS services, this certification is highly relevant to your role.
Ideal Candidate Profile
This certification is suitable for individuals who:
- Have 1–2 years of hands-on experience in data engineering or analytics
- Are familiar with AWS cloud services related to data management
- Want to validate their ability to design scalable, secure, and cost-effective data workflows
- Prefer a role that focuses on solving real-world data problems using cloud technologies
Career Roles
Earning the DEA-C01 certification can boost your credibility and job prospects in several roles, including:
- Data Engineer
- Cloud Data Engineer
- Data Analyst (with a technical focus)
- Business Intelligence (BI) Developer
- Cloud Engineer
- Big Data Developer
- ETL Developer
Whether you are transitioning into a data-centric cloud role or upskilling to stay current, this certification strengthens your positioning in today’s competitive job market.
Skills Required
Before attempting the exam, candidates are expected to be comfortable with:
- Designing and implementing data ingestion pipelines (both batch and real-time)
- Working with AWS services such as S3, Redshift, Glue, Kinesis, Athena, and IAM
- Understanding core data concepts like ETL, data lakes, schema evolution, and partitioning
- Applying security measures including encryption, access control, and data governance
- Monitoring and troubleshooting performance using AWS-native tools
While the exam does not require deep software engineering experience, it does expect a solid grasp of cloud-based data workflows and the ability to make architectural decisions based on cost, performance, and scalability.
Preparation Guide for AWS Data Engineer Associate (DEA-C01) DEA-C01
Preparing for the AWS Certified Data Engineer – Associate exam requires both conceptual understanding and practical experience. Below is a step-by-step study plan to help you prepare effectively and confidently.
Understand the Exam Guide
Before diving into the content, start with the official exam guide provided by AWS. It outlines the domains, weighting, and expectations for each section of the exam. Familiarizing yourself with the guide ensures that your preparation stays focused and aligned with what will actually be tested.
- Link to official guide: AWS DEA-C01 Exam Guide
- Take time to carefully read the descriptions of the five domains
- Note the emphasis on hands-on ability and real-world problem-solving
Understanding these domains helps you prioritize study topics and identify areas where you may need more practice.
Learning Resources
There are several excellent learning platforms and materials to build your knowledge:
- AWS Skill Builder: The official learning portal by AWS offers exam-specific learning plans and labs.
- Online Courses: Platforms like A Cloud Guru, Coursera, and Skilr offer structured DEA-C01 preparation courses. Look for courses that include both video lectures and labs.
- AWS Whitepapers and FAQs: These are must-reads for understanding best practices and AWS design principles. Key whitepapers include:
- AWS Big Data Analytics Options
- AWS Well-Architected Framework
- YouTube Channels: Channels like freeCodeCamp, Stephane Maarek, and AWS Events often feature tutorials, demos, and certification reviews that are extremely helpful.
Hands-on Practice
The DEA-C01 exam is practical in nature, so hands-on experience is critical.
- Use AWS Free Tier: AWS provides a free tier with limited monthly usage. Use this to test services and run small-scale data projects.
- Build Sample Projects:
- Set up a streaming pipeline with Kinesis
- Use Glue for data transformation
- Query datasets using Athena and Redshift
- Manage data lakes with Lake Formation
- Practice configuring security and permissions via IAM
- Store and manage data using Amazon S3
- Try simulating real business scenarios such as ingesting CSV/JSON data, cleaning it with Glue, and querying it via Athena.
Start evaluating with Practice Tests
Taking practice exams is one of the best ways to prepare:
- Why it matters: Practice tests simulate the real exam environment and highlight knowledge gaps.
- Where to find them:
- Skilr mock exams for DEA-C01
- AWS-provided sample questions (available in the exam guide)
- After each mock test, carefully review every question, especially the ones you got wrong. Understand why the correct answer was right, and revisit those topics if needed.
Join Study Groups or Forums
Joining communities keeps you motivated and helps you learn faster through discussion and shared resources.
- Subreddits like r/AWSCertifications often have exam tips, success stories, and recommended study paths.
- Many AWS-focused groups share study material, webinars, and job opportunities.
- Live discussion channels where people share doubts, mock questions, and project ideas in real time.
Engaging with a community can also help you stay updated with any new changes to the exam or AWS services.
Must-Know AWS Services for DEA-C01
| AWS Service | Primary Use Case | Sample Exam-Style Question |
|---|---|---|
| AWS Glue | Automate ETL jobs; transform data for analytics | Which AWS service lets you create serverless ETL pipelines to transform raw data in S3? |
| Amazon Kinesis | Ingest and process real-time streaming data | You need to build a pipeline to process stock market data streams in real time. What should you use? |
| Amazon Redshift | Run fast SQL queries on structured data; data warehousing | Which AWS service is best suited for running complex queries on petabyte-scale data sets? |
| AWS Lake Formation | Build and manage secure data lakes | How can you enforce fine-grained access control over your data lake in S3? |
| Amazon Athena | Query S3-stored data using standard SQL | Which serverless service allows you to query data stored in Amazon S3 without loading it into a database? |
| Amazon S3 | Store raw, processed, and structured data | You want to store both raw CSV logs and processed Parquet files. Which storage service fits? |
| IAM | Manage permissions and access to AWS services | What AWS service lets you control access to AWS Glue and Redshift resources via policies? |
| CloudWatch | Monitor metrics, set alarms, track system health | How do you monitor memory usage and trigger alerts when a data pipeline exceeds thresholds? |
| CloudTrail | Track user actions and API calls for auditing | Which service provides logs of all API activity across AWS accounts for compliance review? |
Tips to Crack the Exam
Success in the AWS Certified Data Engineer – Associate (DEA-C01) exam doesn’t just come from memorizing concepts. It requires strategic preparation and test-taking techniques that help you perform confidently under time pressure. Here are some practical tips to help you clear the exam on your first attempt:
Time Management During the Test
You’ll have 130 minutes to answer around 65 questions, which gives you about 2 minutes per question. Keep an eye on the clock and don’t spend too much time on any single question. If you’re unsure, flag it and come back later. Always complete the first round of easier questions quickly to buy time for the tougher ones.
Use the Elimination Technique
Many questions include multiple plausible answers. When you’re stuck, eliminate the clearly incorrect options first. This narrows your choices and increases your chances of selecting the right one. Look out for answers that are too absolute (e.g., always, never) or don’t fit the scenario described.
Focus on Use-Cases, Not Just Theory
AWS exams are scenario-based, which means the questions will test how you apply concepts, not just if you know them. It’s important to understand when to use Glue over Redshift or why you’d pick Athena for a certain analysis task. Think from the perspective of a real data engineer designing a solution.
Review Case Studies and Real-World Scenarios
Go through AWS case studies and architecture blogs to see how real companies use services like Kinesis, Lake Formation, and Redshift. These examples will help you understand trade-offs in performance, cost, and scalability, which is often what the exam questions focus on.
After the Exam: What’s Next?
Completing the AWS Certified Data Engineer – Associate (DEA-C01) exam is a significant achievement. Once you’ve submitted your test, here’s what you can expect next and how to make the most of your new certification.
When Will You Get Results?
In most cases, you’ll see a pass/fail status immediately after completing the exam. However, the official score report and digital certificate are usually available within 5 business days in your AWS Certification account. Occasionally, AWS may take a little longer if manual validation is required.
Digital Badge and Certificate
After your results are processed:
- You will receive an official certificate in PDF format.
- You’ll also get a digital badge via Credly (formerly Acclaim), which can be easily shared online.
- The badge is verifiable and shows your name, date of certification, and certification level.
How to Showcase Your Certification
Once certified, make sure to update your professional profiles:
- LinkedIn: Add the certification under “Licenses & Certifications” and share your badge post to attract recruiters.
- Resume: Include it in a dedicated “Certifications” section and highlight data-specific AWS tools you’ve used.
- GitHub: If you’ve built hands-on projects during preparation, consider creating a pinned repo or README section linking your projects and mentioning the certification.
This will help you stand out in job applications and prove your practical skills in cloud-based data engineering.
Future Certifications: What’s Next?
Now that you’ve completed the DEA-C01, you might consider leveling up by pursuing:
- AWS Certified Data Analytics – Specialty: Ideal for professionals who want to go deeper into complex analytics and big data architectures.
- AWS Certified Solutions Architect – Associate or Professional: Helps broaden your cloud architecture knowledge, which complements your data skills.
- AWS Machine Learning – Specialty: A great next step if you want to move toward AI/ML roles involving large-scale data.
Final Thoughts
The AWS Certified Data Engineer – Associate (DEA-C01) is more than just a badge — it’s a signal to employers that you understand how to work with data in the real world, using cloud-native tools and best practices. In a data-driven world where companies are rapidly migrating to the cloud, this certification gives you both credibility and confidence to take on complex data engineering challenges.
As you prepare, remember that success in this exam doesn’t come from cramming facts. It comes from building intuition around how to solve business problems using AWS services. Spend time understanding the tools, get hands-on with AWS projects, and practice applying your knowledge to real-world scenarios.
Finally, treat this exam as a milestone, not the destination. Use it to fuel your growth, explore specialized certifications, and take your data career to the next level. You’ve got this.
