Big Data

What does a Data Engineer do? How to become one [step by step]

Data engineering - data collection

In today’s data-driven world, data engineers are indispensable. Many young people who are now planning their careers think about pursuing the career of a data engineer. And as we have quite a lot in common with data engineers (they are a vital part of the Addepto team and data engineering services are at the core of our work), we decided to create this short guide. What do you need to become a data engineer? And what data engineering skills you should master? Let’s find out!

First things first–who is a data engineer? In short, they are responsible for everything technical related to data science. Data engineers construct, design, and maintain the whole IT infrastructure that data scientists and machine learning specialists use in their everyday work. That’s why the list of data engineering skills comprises primarily technical skills, including programming languages (especially Python but also Java, C++, R, and Scala) and SQL databases. As a future data engineer, you will be responsible for ensuring that all the data science and machine learning algorithms and applications work flawlessly on the production level. And since data engineers work closely with data scientists, you will most likely be a part of the larger data analytics team in the company.

What does a data engineer do?

Partly, we’ve already covered this topic–they ensure everything works properly from the technical standpoint. Let’s be more specific, though. The whole list of typical data engineer’s responsibilities is much longer:

  • Designing and developing data platforms and all the data-related tools: Data platform is a broad term that describes the whole infrastructure used to execute data-related goals. Data engineers are responsible for finding the optimal solution and implementing it. It’s the same story with all the data-related tools and applications.
  • Maintaining and improving the data infrastructure: Once the data infrastructure is up and running, it still needs to be monitored, maintained, and improved according to the company’s changing needs and new projects. We could say that data engineer has an ongoing assignment, as long as a given company deals with data science, there will be plenty of work for you. Furthermore, data engineers also make sure that data in their company is organized and prepared for new projects.
  • Dealing with machine learning algorithms: Frequently, data engineers work closely with machine learning specialists and help them devise and deploy machine learning algorithms. That said, it would be extremely useful for you to gain some ML-related knowledge as a part of your data engineering skills.
  • Data visualization: Finally, data engineers work with data visualization tools to produce various reports for stakeholders and management. Truth be told, it’s one of the data engineer’s side jobs, but you have to be aware of it. They are also responsible for developing dashboards, reports, and other data visualization solutions.

How to become a data engineer

The website has made a complete step by step guide on how to become a data engineer. At Addepto, we have similar experiences. Let’s take a look at what you need to do in order to become a successful data engineer:

  1. Obtain a bachelor’s degree. That’s always your starting point. The list of potential fields that will prove useful in this career path comprise computer science, software/computer engineering, math, and statistics. Of course, the more IT-related field, the better.
  2. Don’t wait till the end of college to build experience. Start with some entry-level projects. At this point, you should also finish some side training in order to get additional certificates. Companies and organizations offering training for data engineers comprise AWS (Amazon Web Services), Cloudera, DASCA (Data Science Council of America), IBM, and SAS. You can also visit various online training websites like Coursera and check their offer of data engineering courses and certificates.
  3. Get a master’s degree in a strictly data-science-related field. During your studies, you can try to find a regular-level job in a corporation or a data science company like Addepto.

Moreover, you have to be prepared that the majority of companies looking for data engineers require knowledge extending beyond this field of knowledge. It would be extremely helpful if you had knowledge concerning:

  • Big data management tools: We encourage you to read our article about using big data in everyday work. You will find tons of practical information there.
  • Relational databases: SQL and NoSQL
  • Data pipeline and workflow management tools
  • Cloud computing services: The two leading services are Amazon AWS and Microsoft Azure

And what about other data engineering skills? Focus on these:

  • Data transformation techniques (especially the ETL process)
  • Machine learning libraries and frameworks
  • Data storage solutions (especially designing and building data warehouses)

As you can see, it’s a quite long and challenging road to go. But you can be sure that there will be plenty of work for you in the coming years!

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