ETL & Data Pipelines with Shell, Airflow & Kafka is a practical, hands-on introduction to building automated and scalable data workflows. Designed for aspiring data engineers, analysts, and technical professionals, this course walks you through the essential tools and frameworks used to extract, transform, and load data across modern systems.
 
You’ll begin by working with Shell scripting to create foundational automation and data-processing tasks. From there, you’ll explore Apache Airflow, learning how to orchestrate complex workflows, schedule jobs, and manage dependencies with ease. The course then introduces Apache Kafka, a leading platform for real-time data streaming, where you’ll learn how to build pipelines that handle continuous, high-volume data flows.
 
By combining batch processing, orchestration, and real-time streaming, this course gives you a comprehensive skill set for designing reliable, scalable, and production-ready data pipelines.
 
What You’ll Learn
Build foundational automation workflows using Shell scripting
Design, schedule, and orchestrate pipelines with Apache Airflow
Use Apache Kafka for real-time data streaming and message processing
Develop ETL processes for batch and streaming data
Understand key concepts in pipeline reliability, scalability, and monitoring
Integrate multiple tools to create end-to-end data engineering solutions