How Linux is Used in Real-World Data Engineering

Linux is the backbone of modern data engineering. From running ETL pipelines on cloud servers to managing distributed systems like Hadoop and Spark, proficiency with the Linux command line is non‑negotiable. In this guide, we’ll walk through a realistic data‑engineering workflow on an Ubuntu server – the kind of tasks you’ll perform daily when managing data pipelines, securing sensitive files, and organising project assets. We’ll cover: Secure login to a remote server Structuring a data project with version‑aware directories Creating and manipulating data files (CSV, logs, scripts) Copying, moving, renaming, and cleaning up files Setting correct permissions to protect sensitive data Navigating the file system and re‑using command history 1. Logging into a Linux Server In the real world, data engineers rarely work on their local laptop. Most tasks happen on remote servers (on‑premises or in the cloud). The first step is to securely connect to it using SSH, and put in the password when p