AWS Data Engineering for Modern Analytics

What if your data pipelines didn't break at scale, no surprise bills, no late-night firefights, no silent failures? In a world where cloud-native analytics defines competitive advantage, simply collecting data isn't enough. Enterprises need platforms that are secure, auditable, cost-efficient, and engineered to survive real-world complexity.

This book is your practical blueprint for building production-ready data systems on AWS. It strips away hype and focuses on the reality facing modern data teams: how to architect lakes on S3 with intent, how to run Glue and EMR without waste, how to orchestrate with Step Functions and CI/CD instead of ad-hoc scripts, and how to design pipelines that evolve safely as your business grows.

At its heart, this guide solves the biggest challenge in cloud data engineering-moving from prototypes that "work" to platforms you can trust with mission-critical workloads.

You will learn how to:

• Structure S3 data lakes with the right formats, partitions, and lifecycle rules

• Build incremental ETL pipelines with Glue that handle schema changes and retries

• Implement real-time streaming with Kinesis and Flink for event-driven analytics

• Design secure, governed environments with IAM, Lake Formation, and encryption

• Deliver ML-ready feature pipelines and integrate with SageMaker

• Observe pipeline health, enforce SLAs, and prevent silent data drift

• Deploy reliable infrastructure using Terraform/CloudFormation and automated CICD

Through hands-on labs and real deployment patterns, you'll master the engineering fundamentals behind cost control, operational resilience, metadata design, multi-environment workflows, disaster recovery, and future-proof storage formats like Apache Iceberg.

If you're a data engineer, architect, analytics leader, or cloud practitioner committed to building systems that don't crumble under real workloads, this book will elevate your execution and confidence.

Build with precision. Ship with certainty. Own your data platform, not the other way around.

Get your copy and start engineering AWS pipelines the right way, today.