AWS Data Engineer Roadmap
Free, hands-on AWS labs across S3, Glue, Athena, Lambda, Lake Formation, Redshift, and DMS. Every chapter is a real build in the console, with screenshots for every step.
Introduction to AWS: Console, Regions & IAM
Sign in, lock down your region, and see how an IAM role's trust relationship actually works — the orientation every later lab assumes.
Build an AWS Data Lake with S3, Glue & Athena
Build a serverless data lake by hand — S3, Glue Data Catalog, two crawlers, a PySpark ETL job, and Athena SQL — with a CSV-vs-Parquet cost comparison at the end.
Event-Driven Ingestion with AWS Lambda
Three Lambda ingestion patterns end-to-end — S3 → SQS → Lambda, S3 → Lambda direct, and Lambda-as-ETL — and when each shape fits.
Fine-Grained Access Control with AWS Lake Formation
Lake Formation fine-grained access control — table grants, column filters, row filters, and tag-based access — done entirely from the console.
Federated Queries with Amazon Redshift Serverless
Connect Redshift Serverless to S3 (Spectrum) and live Aurora (federated query), then join both in one SQL statement — no data movement.
Change Data Capture from Postgres with AWS DMS
Capture every INSERT/UPDATE/DELETE in real time with AWS DMS, replicating Postgres CDC to either a second RDS instance or an S3 lake.
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