AWS Certified Data Engineer Associate (DEA-C01) – Complete Training Course
Course Description
AWS Certified Data Engineer Associate (DEA-C01) is an end-to-end training program designed to prepare data professionals, cloud engineers, and analytics practitioners for the AWS Data Engineer Associate certification. This course provides a comprehensive understanding of how to design, build, secure, and optimize data solutions using AWS’s modern data ecosystem.
You’ll gain hands-on experience with data ingestion, transformation, storage, orchestration, analytics, and operational workflows across AWS services such as Kinesis, Glue, Lambda, DynamoDB, Redshift, EMR, S3, Athena, Lake Formation, Step Functions, and more. Through practical labs and real-world scenarios, you’ll learn how to handle structured, semi-structured, and streaming data at scale while ensuring reliability, performance, and governance.
This course aligns directly with the DEA-C01 exam domains and equips you with the technical depth and practical skills needed to succeed in both certification and real-world data engineering roles.
What You’ll Learn
Data Ingestion & Processing
Using AWS Kinesis (Streams, Firehose, Data Analytics) for streaming data
Building ETL/ELT pipelines with AWS Glue, Glue Studio, and Glue Jobs
Working with Lambda for serverless data transformations
Integrating SQS, SNS, and EventBridge for event-driven workflows
Storage & Data Modeling
Designing S3-based data lakes with optimal partitioning and file formats
Using Lake Formation for access control and governance
Working with DynamoDB, document models, and NoSQL best practices
Understanding Redshift design patterns and query optimization
Data Orchestration & Workflow Automation
Creating workflows with Step Functions and managed orchestration tools
Scheduling and chaining pipelines for reliable data operations
Error handling, retries, and operational monitoring
Analytics & Querying
Running interactive and federated queries with Athena
Using Redshift for analytical workloads and warehousing
Leveraging EMR for Spark, Hive, Presto, and big data processing
Security, Governance & Reliability
Encryption, IAM roles, KMS, VPC endpoints, and secure access patterns
Data quality, lineage, cataloging, and schema evolution
Scaling, optimization, and cost-efficient design strategies
Exam Preparation
Domain-aligned study structure
Hands-on labs simulating real exam scenarios
Practice questions and exam-oriented problem solving
Who This Course Is For
Data engineers and cloud engineers
BI developers and analytics professionals
Anyone preparing for the AWS Data Engineer Associate certification
Students and professionals working with cloud data systems