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Part 1

Computer science fundamentals

As a data engineer, you will work most of your time with Linux® and its toolbox. As such, you need to master the basics properly before we can continue. Once you get accustomed to this new environment, we’ll continue with a basic programming course in Go®.

Then we dig deeper into how computers work and how to design and develop the software properly.
In this context, you need to understand the purpose of an operating system and the concepts behind it.
Since we have never been so connected before in the history of mankind, computer networks and, more specifically, the main components and protocols that make up a physical network have to be addressed.
Finally, we introduce the concepts of data transport, data modeling, data storage, and data security.

Parallel to these tracks, we will discuss the impact all these technological evolutions have had and still have on our daily life and work.

In part one, we will focus on the fundamentals:

  • Linux, the shell, and tools
  • Programming101 in Go
  • Operating system concepts
  • Computer networks: i.e., PPP, Ethernet, TCP/IP reference model, devices, …
  • Relational databases
  • Impact of computing

Part 2

Data engineering

Once you have mastered these fundamental concepts, we will start comparing legacy approaches to cloud-native practices as they apply to data-intensive computing and applications.

Data-intensive computing requires a cluster of distributed virtualized computers. In analogy to an operating system on a single computer, new tools are required to manage and monitor these clusters.

In a cloud-native environment, all these clusters are (inter)connected through a computer network, where topics like scalability, availability, reliability, and security by design are essential to understand.

Dealing with the growing complexity and importance of data requires new strategies, algorithms, design principles, and tools that will allow you to handle data delivery “at least once”, “exactly once”, or “at most once” in an economically justifiable manner.

And finally, as we process huge amounts of potential privacy and security-sensitive data in data engineering, it is essential to address data ethics.

In part two, we will focus on:

  • Containers: Docker
  • Container orchestration: Kubernetes
  • Building an in-memory key-value store in Go
  • Cloud-native and hybrid offerings: i.e., AWS, Exoscale,…
  • Event frameworks: i.e. MQTT, Apache Kafka,…
  • NoSQL databases, block storage, object storage,…
  • Automated development: CI/CD
  • Cloud economics
  • Data ethics

Course Outline

Start of the course

In January 2024, you’ll meet your fellow trainees and start learning.


1 month evaluation

Are we still a match after our first 5-weeks of training?


3 months status review

Are you still on track after 3 months or do you need to step up your game?


6 months evaluation

After successful completion of the computer science fundamentals course, we’ll dive deep into the world of data engineering. 


9 months evaluation

Have you finalized the data engineering training successfully?
Congratulations and welcome to Klarrio! Your road to success is now well underway.


All good? Welcome to Klarrio!

Your new career as a junior data engineer can officially start.

Meet our coaches

Meet Bram and Stefano, the coaches behind tutorrio.

What is a Data Engineer?

We like to define Data Engineering (Or more Recently, also called “Platform Engineering”) as putting in place the foundations and plumbing of a building, where the applications reside.

Imagine a grand building that serves as a hub for various applications. This is where the magic happens.
Now think about your smartphone for a moment. When you install apps, you might wonder why an operating system is necessary. The truth is, without an operating system like iOS or Android, those apps won’t have a place to call home.

Apps, whether they’re games, useful tools, or powered by advanced AI, need a solid foundation and access to data. That’s where Data Engineers step into the spotlight. Data Engineers build the operating systems and platforms that provide the structure for apps to thrive. They also ensure the secure flow of data, enabling apps to leverage the necessary information and perform their tasks while maintaining top-notch security measures.

They are the architects of these operating systems, these platforms that welcome third-party apps with open arms. Actually, you have two paths to explore in this digital world: You can specialize in creating those applications, crafting intricate business logic or unraveling the secrets of data science. Or, you can take a different route and become a builder of the recipient platform, the one responsible for constructing the perfect home for all these exciting things.

In the world of Data Engineering, the power of technology and data converge to foster innovation. It’s a realm where imagination meets computation, where data takes center stage, and the possibilities are limitless.

That’s the essence of what we do!

Ready? Apply!

Want to learn more?
Download a detailed information packet
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