Introduction

Modern data engineering systems rely heavily on reliable, scalable, and consistent environments for processing large volumes of data. ETL (Extract, Transform, Load) pipelines often involve multiple technologies such as databases, APIs, workflow orchestration tools, and programming frameworks that must work together seamlessly across development, testing, and production environments.

Docker was created to solve these challenges through containerization. It allows developers to package applications together with all their dependencies into lightweight, portable containers that can run consistently across different environments.…