Start here in AWS
The most useful guides in this topic, not just the most recent.
AWS Guides & Tutorials
AWS for data engineers — S3, EC2, Lambda, Glue, Redshift, Athena, EMR and the certification roadmap that gets you hired.
AWS articles
AWS Roadmap 2026 for Data Engineers
What to learn on AWS as a data engineer, in the order data moves through a pipeline: S3 and IAM, Glue and Athena, Glue jobs, Redshift, Step Functions, streaming and governance, with something to build at every stage and a clear test for when you are done.
Amazon S3 Explained: Storage, Classes and Best Practices
How Amazon S3 storage classes differ — minimum storage duration, minimum billable size, retrieval time — and a four-question method for putting each dataset in the right class, with lifecycle and security defaults for a data-engineering bucket.
Amazon EC2 Explained: Instances, Types and Pricing
Amazon EC2 is the virtual-server service underneath much of AWS. This guide explains instances, AMIs and storage, decodes instance type names such as r5.4xlarge and compares memory per vCPU across families, sets out On-Demand, Savings Plans, Reserved and Spot purchasing, and shows which charges continue after a stop.
AWS Lambda Explained: Serverless for Beginners
AWS Lambda runs your code in response to events without servers to manage. This beginner's guide explains the handler, events and triggers, what an execution environment is and why initialisation code runs once, the limits that shape what Lambda is for, how billing works, and where it fits in data pipelines.
AWS Glue Tutorial: Serverless ETL on AWS
A beginner's tutorial on AWS Glue, the serverless ETL service: what each component does, the catalog, crawlers, jobs, triggers and workflows, how they fit into one pipeline, a crawler, job and nightly schedule defined in code with boto3, how billing works, and the settings to get right on day one.
Amazon Redshift Explained: The Cloud Data Warehouse
An introduction to Amazon Redshift, AWS's data warehouse: how a leader node, compute nodes and slices run a query in parallel, why data is stored in columns, how managed storage separates compute from storage, Serverless versus a provisioned cluster, how it differs from PostgreSQL, and what to learn first.