Edoxi’s 40-hour Online AWS Data Engineer-Associate(DEA-C01) Certification is a globally oriented training solution designed for learners who want to develop advanced, industry-ready data engineering skills in the cloud. Our intermediate-level AWS Data Engineer-Associate training focuses on building scalable, secure, and modern data architectures that support today’s international digital ecosystems. Whether you are part of a global IT team, a data engineering department, an analytics unit, or a cloud-focused organisation. Our training equips you with the essential competencies needed to thrive in an increasingly data-driven world.
We emphasise practical, hands-on learning through instructor-led sessions and real-world AWS lab environments. Participants work directly with globally deployed AWS services, including Amazon Kinesis, AWS Glue, Amazon Redshift, Amazon S3, and Amazon EMR. Our AWS Data Engineer-Associate course also explores automation using AWS Lambda and Step Functions, along with advanced analytics through Amazon Athena and QuickSight. These practical experiences prepare learners to design, ingest, store, transform, and analyse data efficiently while adhering to industry-recognised security and governance frameworks. Here are the details of the AWS Data Engineer-Associate Certification Exam:
| Exam Criteria | Details |
| Exam Code | DEA-C01 |
| Exam Name | AWS Certified Data Engineer Associate |
| Duration | 130 minutes |
| Number of Questions | 65, Multiple Choice |
| Passing Score | 720/1000 |
| Fees | $150 |
| Certification Validity | 3 Years |
| Recertification | Required 3 Years |
| Exam Administration Authority | Pearson VUE |
Edoxi’s globally valued AWS Data Engineer-Associate certification is recognised across leading enterprises and cloud-driven industries. The curriculum addresses both batch and streaming data architectures, ETL/ELT workflows, and integrations with modern machine learning processes. By aligning training with global industry standards, Edoxi ensures that professionals stay competitive and relevant in the rapidly evolving international cloud and data landscape.
You can practise directly within authentic AWS services using dedicated lab environments. You also gain hands-on experience with real AWS data engineering workflows across the cloud ecosystem.
You can access detailed courseware, student guides, and PDF references covering Glue Crawlers, PySpark/Scala, Redshift Spectrum, and other essential AWS data engineering tools.
You can participate in interactive presentations and scenario-driven group activities. You also develop stronger problem-solving skills and gain exposure to real-world data engineering challenges.
You can complete practical hands-on labs and end-to-end pipeline projects with documented outputs. You also build a professional portfolio showcasing your AWS data engineering implementations.
You can work with foundational AWS services such as Kinesis, Glue, Redshift, EMR, and Lambda. You also gain the ability to design and operate modern data architectures using globally adopted cloud technologies.
You can prepare effectively for the AWS Certified Data Engineer – Associate (DEA-C01) exam through targeted, objective-aligned training. You also gain competencies mapped directly to AWS’s global certification standards.
Professionals working with data who want to expand their skillset to include cloud-based data pipeline development and management on AWS.
Developers with experience in data transformation processes are looking to transition their skills to AWS cloud-native solutions.
Technology specialists with a strong foundation in database concepts and SQL who want to specialise in modern data architecture.
ML specialists seeking to understand the data engineering foundations that support effective machine learning pipelines.
Technical professionals with cloud experience wanting to specialise in the high-demand field of data engineering.
Technology professionals looking to move into the rapidly growing field of cloud data engineering with AWS expertise.
Edoxi’s 40-hour Online AWS Data Engineering course delivers fully practical, subscription-based AWS Lab experiences. Here are the major hands-on labs in the AWS Data Engineer-Associate Training
learn to build a real-time streaming pipeline using Amazon Kinesis Data Streams to capture, process, and analyse live data from multiple sources, generating immediate insights for decision-making.
Automated workflows are configured by scheduling AWS Lambda functions with Amazon EventBridge. Serverless data processing tasks are implemented to trigger at predefined intervals.
Sensitive information in datasets is discovered using Amazon Macie, and encryption controls are applied with AWS KMS to secure Amazon S3 buckets and EBS volumes, ensuring data privacy and compliance.
Data extraction, transformation, and loading (ETL) are performed using AWS Glue, with Amazon S3 serving as both the input and output storage. Processed datasets are cleaned, enriched, and published.
A fully functional Amazon Redshift data warehouse is built, including schema design, workload optimisation, credential security, and performance monitoring for scalable analytics.
An Amazon EMR cluster is set up to run Apache Spark jobs for processing large-scale datasets. Distributed computing techniques are applied to support efficient big data analytics in production environments.
Completing Edoxi’s 40-hour AWS Data Engineering–Associate certification course provides a structured pathway to high-growth roles in cloud and data engineering. These roles are increasingly in demand as organisations across industries adopt AWS for large-scale data management and analytics.
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Join Edoxi’s AWS Data Engineer-Associate (DEA-C01) Course
Edoxi’s 40-hour AWS Data Engineer–Associate Certification Training provides practical, industry-ready cloud skills aligned with global data engineering standards. Here are the major reasons why professionals and organisations choose us for AWS Data Engineering training
Edoxi’s curriculum integrates official AWS best practices with real industry scenarios, ensuring you build job-ready skills that can be immediately applied within modern data engineering environments.
Our AWS Data Engineer-Associate classes are led by experienced AWS professionals who bring deep real-world expertise in data pipelines, cloud architecture, automation, and large-scale data systems.
Our AWS Data Engineer-Associate course follows a structured learning pathway with guided practice, hands-on labs, and targeted exam preparation to help you confidently pass the AWS Data Engineer–Associate certification.
Edoxi is widely recognised for delivering AWS and Azure training for government entities, private organisations, and large enterprises across Africa and the Middle East.
Our programme connects seamlessly with other AWS specialisation tracks, enabling learners to progress into advanced cloud, analytics, and architecture roles.
Edoxi maintains a strong presence across the GCC, including the UAE, Saudi Arabia, Qatar, and Oman and continues to deliver successful cloud training programmes across European and international markets.
Our mentors are leaders and experts in their fields. They can challenge and guide you on your road to success!
Manish Rajpal
Manish is a passionate Corporate Trainer, AI Consultant, and Cloud Solutions Architect. He empowers clients across the globe to build and maintain highly available, resilient, scalable, and secure solutions, now with a growing emphasis on AI-powered architectures. With over 15,000 professionals trained, Manish specialises in technologies including Amazon Web Services, Microsoft Azure, Microsoft Copilot and GitHub Copilot and increasingly, AI and Machine Learning.
Manish has led research and workshops focused on integrating AI into cloud environments, exploring use cases like intelligent automation, natural language processing, and responsible AI practices.
Here are the major international locations where Edoxi offers AWS Data Engineer-Associate(DEA-C01) Course
AWS Data Engineer-Associate (DEA-C01) is moderately more challenging than SAA-C03 because it focuses deeply on data pipelines, ingestion frameworks, transformations, and workflow optimisation. It complements DAS-C01 but does not replace it—DAS-C01 covers deeper analytics and BI workloads, while DEA-C01 is focused on data engineering and pipeline implementation.
