AWS Certified Data Engineer – Associate (DEA-C01)
Intermediate Level
Demonstrate your expertise in designing data models, managing data lifecycles, and maintaining data quality.
The AWS Certified Data Engineer – Associate certification validates your expertise in core AWS data services, showcasing your ability to ingest, transform, and orchestrate data pipelines. It also assesses your proficiency in applying programming concepts, designing data models, managing data lifecycles, and ensuring data quality.
Learn the concepts, strategies, and best practices for designing a cloud-based data warehousing solution with Amazon Redshift in this course.
This Data Engineering on AWS course teaches how to ingest, store, and transform data in a data warehouse using Amazon Redshift. Key topics include:
- Amazon Redshift's purpose, features and capabilities.
- Designing solutions with AWS best practices
- Performance tuning, orchestration, security and monitoring
AWS Certified Data Engineer – Associate (DEA-C01)
Category
Associate
Exam Duration:
130 minutes
Exam Format:
65 questions; either multiple choice or multiple response
Cost:
150 USD
Visit Exam pricing for additional cost information, including foreign exchange rates
Language Offered:
English, Japanese, Korean, Portuguese (Brazil), and Simplified Chinese
Testing Provider:
Pearson VUE testing center or online proctored exam
What are the key skills measured:
- Data Ingestion and Transformation (34% of scored content)
- Data Store Management (26% of scored content)
- Data Operations and Support (22% of scored content)
- Data Security and Governance (18% of scored content)
Who is this for?
- Data Engineer
- Data Architect
Showcase proficiency in architecting scalable data models, overseeing end-to-end data lifecycle management, and enforcing robust data quality assurance protocols.
93% of Chief Data Officers say data strategy is crucial to generating value from generative AI
AWS for Data – CDO Agenda 2024
More than 50% of organisations believe their data foundation is not ready.
Scaling Generative AI for Value: Data Leader Agenda for 2025
90% of organisations with AWS Certified staff report improved cloud workforce productivity.
Understanding the Value of AWS Certifications to Organizations
Validate In-Demand Data Engineering Skills:
This certification validates your expertise in core AWS data services, including data ingestion, transformation, orchestration, and pipeline management. It demonstrates your ability to design data models, manage data lifecycles, and ensure data quality, making you an asset in the data-driven industry.
Master AWS Data Services and Best Practices:
The certification equips you with hands-on skills in AWS data services like Amazon Redshift, Glue, Kinesis, and Lambda. You’ll also learn to apply AWS best practices, including the Well-Architected Framework, to design efficient and scalable data solutions.
Enhance Career Opportunities and Credibility:
As organizations increasingly rely on cloud-based data solutions, AWS-certified professionals are in high demand. This certification enhances your credibility and opens doors to roles like Data Engineer, Cloud Data Architect, and Data Analyst.
Stay Competitive in a Growing Field:
With the rapid growth of big data and cloud computing, this certification ensures you stay competitive in the job market. AWS certifications are recognized globally, giving you an edge in both local and international opportunities.
Why choose Trainocate?
Trainocate has been recognized as the AWS Training Partner of the Year from 2022-2025, highlighting its excellence in cloud skills development and commitment to digital transformation globally. This award reinforces Trainocate’s reputation as a top-tier AWS training provider, ensuring learners receive industry-recognized education with the latest cloud technologies.
By choosing Trainocate, participants benefit from an award-winning institution dedicated to equipping professionals with in-demand AWS skills to drive career growth and business innovation.
Ready to build your data engineering expertise with AWS?
Complete the form below to register your interest.
Frequently Asked Questions (FAQs)
1. Who should take this exam?
The ideal candidate for this exam is familiar with AI/ML technologies on AWS and uses, but does not necessarily build AI/ML solutions on AWS. If you are new to IT and AWS Cloud, you should first start with AWS Cloud Practitioner Essentials or AWS Technical Essentials. Certified individuals holding the AWS Certified Cloud Practitioner or an Associate-level AWS Certification do not need to take the foundational cloud courses and can start with free AI foundational training also included in the Exam Prep Plans.
2. How will the AWS Certified Data Engineer - Associate help my career?
This is an in-demand role with a low supply of skilled professionals. AWS Certified Data Engineer – Associate and accompanying prep resources offer you a means to build your confidence and credibility in data engineer, data architect, and other data-related roles.
3. What certification(s) should I earn next after AWS Certified Data Engineer - Associate?
The AWS Certified Security – Specialty certification is a recommended next step for cloud data professionals to validate their expertise in cloud data security and governance. View AWS Certification paths to learn more and plan your AWS Certification journey.
4. What jobs can AWS Certified Data Engineer – Associate help me prepare for?
The certification is primarily aligned with data engineer roles but is also relevant to data architects and professionals responsible for cloud-based data platforms and pipelines. AWS specifically identifies data engineer, data architect and other data-related roles when describing its career value.
It can be particularly relevant for professionals responsible for ETL pipelines, data lakes, data stores, data modelling, data quality and cloud data operations.
5. Is AWS Certified Data Engineer – Associate useful for AI careers?
Yes, particularly for professionals who want to work on the data infrastructure behind AI and machine learning systems. AWS emphasises that data quality, governance and operational pipelines are fundamental to successful generative AI initiatives.
The certification itself does not validate machine learning model training or inference. Those tasks are explicitly outside the DEA-C01 scope. Its value lies in building and managing the data foundations that analytics, ML and AI systems depend on.
6. How does this certification align with emerging data trends like real-time pipelines and cloud data governance?
The AWS Data Engineer certification covers:
- – Streaming ingestion and processing services (e.g., Kinesis, Lambda)
- – Schema design and transformation using Glue and Redshift
- – Data security and compliance via IAM, encryption, and secure storage
Malaysia’s national cloud and AI policies emphasize secure data utilization, while enterprises are adopting real-time insights through dashboards and predictive analytics. The AWS certification ensures candidates are skilled at building these architectures with best practices for scalability and security.
Pro Tip: Create a small proof-of-concept that ingests streaming data into Redshift or S3 and visualize it via QuickSight—this practical sample can greatly strengthen your portfolio.
