AWS Certified: Data Engineering Associate (DEA-C01)
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- Authorised Pearson Vue Test Centre
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- Exam Insurance included
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- Flexible 0% payment plans available
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- Study in-person, online or self-paced
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- Expert 1-on-1 Instrustor Support & Exam Preparation
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- Boost your earning potential & career progression
80 – 100 hours
Intermediate
AWV4DDA

Key Details
The AWS Certified Data Engineer – Associate (DEA-C01) certifies technical proficiency in designing, building, and maintaining data pipelines on AWS. Aimed at data engineers and technical specialists, this qualification covers data ingestion, transformation, storage optimisation, data governance, and analytics pipeline orchestration. Candidates master native services such as AWS Glue, Amazon Redshift, and Amazon S3. Equipping your engineering team with this certification ensures your organisation can reliably convert raw operational data into secure, structured, and actionable business insights, supporting data-driven decision-making and robust analytics infrastructure.
- Module 1: Data Ingestion and Transformation – Covers the design and implementation of batch and streaming data pipelines using services such as AWS Glue, Amazon Kinesis, AWS DMS, and AWS Step Functions. Candidates learn to extract, transform, and load (ETL) data from diverse sources while maintaining optimal workflow throughput.
- Module 2: Data Store Management – Focuses on selecting, configuring, and optimising data storage solutions across Amazon S3, Amazon Redshift, Amazon DynamoDB, and Amazon RDS. Candidates examine schema design, data partitioning, indexing, and cataloguing techniques to align storage structures with operational and analytical requirements. Module 3: Data Operations and Support – Details methods for automating, monitoring, and troubleshooting data processing workflows using Amazon CloudWatch, AWS EventBridge, and performance tuning tools. Emphasis is placed on cost management, query optimisation, and maintaining data pipeline health across production execution cycles. Module 4: Data Security and Governance – Teaches techniques for implementing data access controls, encryption, and governance policies using AWS Lake Formation, AWS IAM, AWS KMS, and AWS Glue Data Catalog. It prepares practitioners to enforce compliance, protect sensitive data, and manage metadata auditing across data lakes and warehouses.
Candidates validate their ongoing progress through formative assessments, including interactive knowledge checks, and simulated exam practice quizzes with detailed diagnostic feedback. Final validation is achieved through the official, invigilated AWS Certified Data Engineering Associate (DEA-C01) examination, comprising 65 scenario-based multiple-choice and multiple-response questions delivered over 130 minutes. The assessment thoroughly evaluates candidates’ practical problem-solving capabilities, requiring them to analyse real-world architectural challenges and execute optimal data engineering strategies in live cloud environments.
Candidates are positioned to immediately step into high-impact industry roles such as Cloud Data Engineer, Big Data Architect, Business Intelligence Engineer, and Analytics Engineer across enterprise and commercial sectors. The qualification establishes a strong foundation for rapid career progression into senior technical lead or solution architecture positions within cloud-first organisations. Furthermore, achieving this associate credential serves as a direct gateway toward advanced domain-specific accreditations, including the AWS Certified Solutions Architect – Professional and specialised machine learning or security certifications.
Candidates should ideally possess at least 1–2 years of practical experience with AWS cloud services alongside a working knowledge of SQL, data modelling, and basic scripting languages. Formal technical prerequisites are not mandatory, as applicants with equivalent professional backgrounds in database administration, software engineering, or data analytics are welcomed via Recognition of Prior Learning (RPL). Prospective candidates lacking formal cloud credentials can leverage lived workplace experience in managing ETL pipelines or relational databases to gain direct entry into the qualification programme.
- Training
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