Data Ingestion and Pipeline Orchestration on AWS

Modern organizations rely on timely, high-quality data to drive decisions, but managing complex data flows at scale can quickly become overwhelming. This text-based course guides you through the foundational concepts and practical steps of building automated, event-driven pipelines on AWS. You will learn to ingest, transform, and coordinate data workflows efficiently, moving from manual processes to fully automated systems. What you'll learn: • Understand core data ingestion patterns, batch optimization techniques, and schema evolution. • Configure AWS Glue crawlers and jobs to transform raw data into optimized formats. • Orchestrate complex, multi-step data workflows using Step Functions. • Implement event-driven ingestion triggered automatically by S3 events. • Apply modern data lakehouse patterns, including Apache Iceberg integration with AWS Glue. • Design error-handling and retry mechanisms for robust, production-ready pipelines. Starting with essential terminology and data engineering architectures, this course provides clear written explanations and structured walkthroughs. You will learn how to configure triggers, write transformation scripts, and manage workflow states step by step. This course is designed for aspiring data engineers, cloud developers, and database administrators looking to build reliable data pipelines. No prior AWS data engineering experience is required, though a basic understanding of SQL and Python is helpful. Start reading today to master the foundations of cloud-based data orchestration.