Data Engineering on AWS
Learn how to build data lakes, set up ETL processes using AWS Glue, securely store data in Amazon S3, and perform analytics with Amazon Athena.
Hands-on AWS data engineering training for teams working on data lakes, warehousing, streaming, analytics, and modern pipeline architecture.
Use these AWS data engineering tracks to build practical capability in ingestion, warehousing, streaming, analytics, and platform design.
Learn how to build data lakes, set up ETL processes using AWS Glue, securely store data in Amazon S3, and perform analytics with Amazon Athena.
Deep-dive advanced training focusing on building robust, scalable data ingestion and processing pipelines using services like Kinesis, DynamoDB, and Redshift.
Master the construction and management of secure data lakes. Create centralized repositories with AWS Lake Formation and standardize permissions.
Efficiently process massive datasets. Learn to manage EC2 compute instances, configure AWS Batch jobs, and utilize EMR for large-scale cluster processing.
Optimize querying and dashboarding securely. Focus entirely on Amazon Redshift cluster configuration, data migration, and workload management.
Navigate the AWS database ecosystem. Choose the right database (Aurora, DynamoDB, DocumentDB) for your schema and scale performance securely.
Implement real-time data architectures. Master Amazon Kinesis and MSK (Managed Kafka) to capture, process, and store streaming telemetry rapidly.
Use this track when the team needs stronger capability in data lakes, warehousing, streaming, and AWS-native analytics.
Best for teams building ingestion, ETL, warehousing, and analytics workflows on AWS managed services.
Best for organizations modernizing fragmented data stacks and needing practical AWS data engineering capability fast.
Add assessments and optional virtual proctoring when readiness reporting and controlled evaluation matter.
Yes. This page is focused on data lakes, warehousing, streaming, orchestration, and analytics rather than general cloud coverage.
Yes. The learning path can be aligned to your AWS services, technical depth, team roles, and readiness goals.
Use pre/post assessments and virtual proctoring when you need controlled validation instead of attendance-only reporting.