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DevOps for Data Engineers: What You Need to Know

If you’re thinking about getting into data engineering, you’ve probably heard the term ‘DevOps’ mentioned. But what is it, why is it relevant to data engineers, and how do you learn those skills? 

What Is DevOps?

At a simple level, DevOps is about building, deploying, and running pipelines and applications smoothly. It combines development and writing code (Dev) with operations, or running systems (Ops).

Once you’ve written some code, DevOps helps you:

  • Get your code running in the real world and on the cloud
  • Keep it reliable
  • Update it without breaking things

Why DevOps Matters for Data Engineers

Imagine you’ve built a data pipeline on your laptop. It works perfectly, but that’s not actually enough. It will need to run every day, with more data, and be usable by other people. 

For data engineers, this means taking your data pipelines and making sure they:

  • Run automatically
  • Handle real-world data
  • Scale when needed

DevOps gives you the tools to do so, helping you move from ‘This data pipeline works locally on my machine’ to ‘It works reliably in the cloud for everyone.’ 

Overall, DevOps is the difference between being able to build an isolated data project, and being able to run a full data system like a professional.

What You Need to Learn

There are some key DevOps-related skills that you need to know to work efficiently as a data engineer.  

These are all covered on weeks 5 and 6 of Northcoders’ Data Engineering, AI & Machine Learning Bootcamp, which trains beginners to become junior data engineers. 

  1. Running Code in the Cloud (Compute)

You need to be able to run your code on remote servers, not just locally on your own computer.

You’ll work with:

  • EC2: Think of it as renting a computer in the cloud
  • Lambda: Running small bits of code without managing a server

Why this matters:

  • Your data pipelines can run anytime
  • You’re not dependent on your laptop
  • It’s how real companies operate
  1. Storing Data Properly (Cloud Storage)

Data needs a safe, organised place to be stored in.

You’ll use:

  • S3: Store files (like datasets, logs, outputs)
  • RDS: Store structured data in databases

Why this matters:

  • Your data is secure and accessible
  • You can handle much larger datasets
  • Teams can share and use the same data
  1. Infrastructure as Code (IaC) with Terraform

Instead of manually setting things up, you can write code that builds your infrastructure for you.

With Terraform, you can:

  • Create servers
  • Set up storage
  • Configure systems

Why this matters:

  • You can recreate your setup anytime
  • Fewer mistakes
  • Everything is consistent and repeatable
  1. CI/CD (Continuous Integration & Deployment)

This is about automating your workflow. Instead of manually updating your project every time you make a change, you can:

  • Push your code
  • Tests run automatically
  • Your project updates automatically

Why this matters:

  • Saves time
  • Reduces errors
  • Keeps everything up to date
  1. Orchestration (Making Everything Work Together)

Data pipelines often have multiple steps:

  1. Extract data
  2. Transform it
  3. Load it somewhere

Orchestration tools help you:

  • Run these steps in the right order
  • Handle failures
  • Schedule jobs

Why this matters:

  • Your pipelines run reliably
  • You don’t need to manually trigger everything
  • It scales easily as your project grows

Bringing It All Together

DevOps might sound like a big, complicated topic, but for data engineers, it’s really about one thing: making your data projects work in the real world. 

If you want to build systems that companies actually use, not just projects that sit on your laptop, these skills are essential.

If you’re excited about turning data into real, working systems, through the Data Engineering, AI & Machine Learning Bootcamp, you’ll understand how to:

  • Deploy a real data application
  • Store and manage data in the cloud
  • Automate workflows
  • Build systems that actually run in production

You don’t need any tech experience to join the bootcamp, only foundations in Python. If you’re new to Python, Northcoders will give you access to free materials to learn what you need from scratch in your own time. 
If you’re already an experienced Python developer familiar with databases and looking to upskill in Cloud Engineering and DevOps specifically, Northcoders also offers a 2-week Upskilling in Cloud Engineering and DevOps Course.