Data Engineer certificates

Before starting to talk about which certificate is more beneficial than others, let’s discuss about the purpose of certification in general. Why do you need it? According to a dictionary:

ℹ️ Certificate (specifically): a document certifying that one has fulfilled the requirements of and may practice in a field.

Basically, certificates prove to one person that another person has knowledge*.* But when do you need to prove that you have a knowledge?

If you are currently working in a company, you need to provide results. Company needs a profit, rather than smart philosophical discussions. So companies can check only your knowledge, when they can’t estimate or verify your performance or potential profit that you could bring.

So when does this situation happen, prompting the company to assess your knowledge? During the interview process, particularly in the technical round. However, using developers to conduct live coding interviews or assess home assignments can be expensive for the company. To address this, companies filter a large number of candidates in the first round of interviews aka HR screening.

HRs, while looking for a good candidate for their positions, see a lot of CVs and resumes: Principal Data Engineer, C++ Intern, or Alien from Mars. However how can they select the best candidate out of 200 applicants? One way to show your qualifications to a recruiter during the HR screening round - certificates.

Certifications’ Value

Regularly, I monitor conferences, job posting, and podcasts to stay updated on useful tools for Data Engineer. Obviously, you’ll notice, that some technologies are used more often than other. Just look on the picture below:

Now, you probably won’t surprise, why I chose certain certificates. Of course, there could be specific openings in different fields where knowing supply chain for a retail company or having a second medical degree for a healthcare company would be a big plus. However, in general, having an AWS certificate (i.e., knowing AWS) gives you a broader range of vacancies than knowing Arduino or FreeRTOS.

Top S+ tier

Why AWS and not Azure or GCP? Well… The answer is market demand. Almost 70% of vacancies are used AWS (In Germany in 2025).

And why Snowflake and not Databricks? That's a good question, because Databricks becomes more popular every day. There are some debates among developers on LinkedIn and Medium about whether Databricks is faster than Snowflake or vice versa (for example: dataricks-vs-fabrics-vs-snowflake and databricks-vs-optimized-snowflake).

However, considering the job market in Germany as of January 2025, Snowflake is more prevalent than Databricks.

A tier

Next, I included Databricks, Azure, and GCP. Some companies require these technologies or a general understanding of cloud concepts. Most of the time, the main differences among cloud services lie in the names of the services.

B tier

Here, I included the dbt tool. It has just started to appear in the German market, and some companies already list dbt as a requirement for (Senior) Data Engineer positions.

C Tier

Finally, all other possible certificates fall here. For example, having an Airflow certificate is fine. However, if you’ve worked with Airflow before, you probably know that learning Airflow isn’t very difficult, and in my opinion, getting a certificate for it is overkill. I suggest obtaining a certificate in one of the previously mentioned technologies instead.

Conclusion

To conclude, I’d say one simple thing: you need a certificate if you:

• Don't have real experience and have only used the technology in your pet projects.
• Your CV is rejected most of the time during the initial HR screening interview.
• Want to fill a knowledge gap in a technology, and during exam preparation, you will go through books, training videos, and practice exams, which will help you 100% with that.