Data engineer salaries in Germany 2020

TL;DR: the expected annual gross salary for a junior or mid-level data engineer in Germany is between €45.000-75.000 with a steep increase after a couple of years in the field.

Below a rundown done in August 2020 based on secondary sources from across the internet. This has been verified by our primary research with stakeholders of the Berlin data ecosystem. (Note: if you don’t like the inconsistent structure of the below spreadsheet, you are not alone.)

Data Engineer Salary Germany 2020

Click the links in the Source column to see the the referenced website. Please note, the above information is subject to change.

Things you should know when looking at these figures:

• Expected salaries are not advertised in job listings in Germany, and most companies are highly secretive about this question which adds a lot of inefficiencies to the job search.

• The listed salaries are before taxes, which are determined by various factors. Here's one of the websites helping you calculate what your net salary expectations should look like.

• There are considerable regional differences in cost of living within Germany, make sure to adjust the above figures accordingly. Also, you'll find that there is a major mismatch between what a data engineer makes in Silicon Valley compared to Europe in general: the job markets, tax structures and the cost of living are just so different, that a comparison hardly makes sense.

• There is an upwards trend in salary average and the number of open positions for engineering roles. It should also be noted, that salaries increase with a higher level of seniority much faster than for most other positions, and that the starting salaries for more commoditized engineering positions (e.g. frontend developer) are usually significantly lower than for data engineering roles.

Some considerations for your job search:

• Experience with some specific tools or programming language, background in a certain industry, prior experience in coding or even with managing people have a strong positive impact on salary expectations. Use that when negotiating.

• The scope of the data engineer's role is broad, which is one of the reasons why the position often runs under a different name: machine learning engineer, BI engineer, backend engineer data platforms, data lead etc., furthermore some companies are looking for engineers for using specific tools: Spark engineer, Hadoop engineer etc.

• The career path is also not straightforward in terms of naming conventions for more senior positions, so senior data engineer, data architect, big data architect, head of data etc. are also keywords one should check.

• Do your research: check out local job platforms, job metasearch engines, glassdoor and kununu for company reviews (these platforms can save you from some employer-induced PTSD), and make sure to also read the latest news about the organisation you are considering joining.

• Salary is not everything: when interviewing, ask about team structure and who you are supposed to report to, career paths, stack and learning opportunities. Having a strong mentor can bring you more value on the long run than a few more euros.

• Keep on learning, but even more importantly: keep on working. Create a hands-on portfolio that stands out, experiment with tools and contribute to open source projects to show your skills.

Data engineering is an accessible career path that involves competencies that most career advisors and recruiters would consider essential for the upcoming decades. Regardless if you are a generalist or a specialist, working in tech or any other sector, understanding the flow of data and how to manage it makes any employee into an asset.