Getting the Google Cloud Data Engineer Certification

After getting the Associate Cloud Engineer certification I wanted to go deeper on the data side, so I went for the Professional Data Engineer exam. As usual I kept all the materials I gathered in a public repo: ovimihai/google-cloud-data-engineer-training.

Here is the short version of how it went.

The exam

The Professional Data Engineer certification is all about designing data processing systems, building and operationalizing pipelines, and doing machine learning on Google Cloud. The two pages worth bookmarking from day one:

• Exam Details
• Exam Topics

The learning path

I didn’t jump straight into the exam. I went through the Get GCP Certified 2023 Program, which is structured in stages:

1. Fundamentals – I got Cloud Skills Boost free for 7 days and only had to finish 3 labs to unlock the next step.
2. Professional Data Engineer Journey – the actual target. This time the free Cloud Skills Boost access lasted 2 months, and finishing two badges got me a free exam voucher.

The single most useful tip carries over from the Associate exam: the free Cloud Skills Boost access and the free exam voucher are real. Finish the required badges and you basically get the exam paid for.

Where you learn

Everything happens on Google’s own Cloud Skills Boost platform. It mixes short courses with hands-on labs that spin up real (temporary) GCP projects, so you actually build pipelines with BigQuery, Dataflow, Pub/Sub and friends instead of just reading slides.

Cheat sheets I kept open

These were the tabs I always had open while studying:

• GCP Services cheat sheet
• Smart Analytics
• AI & ML products
• Databases
• gcloud CLI cheat sheet (PDF)

I also went through a set of sample questions to get a feel for the exam style before booking the real thing.

Worth it?

Definitely. The Data Engineer track is heavier than the Associate one — there is a lot of “which service for which job” decision making — but the hands-on labs make it stick. By the time you sit the exam you’ve already moved data around, built streaming and batch pipelines and trained a model or two in a safe sandbox.

If you want my full notes, the learning plan and the lab breakdowns, grab them from the repo: google-cloud-data-engineer-training.