How I Passed My GCP Professional Data Engineer Certification in 2024 (Q4)
Lessons, resources, and strategies I used to nail the GCP Professional Data Engineer exam in 2024.

After a solid three months of 4:30 am wake-ups, I finally took the Google Cloud Professional Data Engineer Exam and passed it. If I had to sum up my path to getting certified in one word — persistence.
It was tough, I’m not gonna sugarcoat it. It also sucked at times! There were easy days and hard days. Sometimes it felt like being kicked down the stairs and asking yourself, what’s the point? Progressing and improving as a Data Engineer means always pushing yourself to learn and finding a way past those momentum killers.
I also took the exam to prove a point to myself.
That point being — it’s up to YOU to self-educate, no one else (this is a lesson I’ve had to relearn time and time again in my career). You can’t sit around waiting for someone to do it for you.
I got invited by Google (twice) to their Google Cloud certification program where they help you get certified in 10 weeks — for free. The only cost is your time. Sounds awesome, right? Sounded like a win-win to me, but I soon realized that if you don’t tick the boxes or lay a golden egg, you ain’t getting on the ticket. I’ve been stuck on that waitlist for about 6 months — no reason why, no notification, no updates, nothing — stuck behind some kind of invisible wall.
So I said to myself, f*** it. I’ll do it myself, like I’ve always had to do.
So I did.
The Certification Debate
If you’re reading this because you want to improve as a Data Engineer, I say go for it. Take the exam — I did, and I’m glad I did. I got exposed to a whole lot more of the GCP ecosystem. I learned a lot about things I don’t get exposed to in my day-to-day job.
I will say this though: the exam doesn’t do Data Engineers any favors and pours fuel on the fire of the ‘unicorn’ Data Engineer — you cannot be expected to be an expert at everything this exam throws at you (if you are reading this, Google, get real).
On certification, I think they get a bad rap in the industry (normally from people who have never done them). My outlook on them is this — anything that helps you grow and learn is a win in my book. What’s not a win is saying you’re going to do something, like signing up for a course, a bootcamp, or an exam, and not following through — the only dressed up word I
know for that is — dumb.
How Did I Prepare?
I’ve been working with cloud infrastructure for most of my career, mainly in AWS, but for the last two years, solely in the GCP ecosystem. I took the Associate Cloud Engineer Exam last year, so I had a good feel for how the exam would be set up.
I followed a similar approach to how I passed that exam (see resources below). For those preparing for the exam, here are the resources I used, and the things that you should focus on.
Here’s What Was in the Exam
The Q4 2023 exam includes new topics like:
✅ Datastream, Dataform (who names these things? 🤔)
✅ Data Catalog, Dataplex, Sensitive Data Protection.
✅ BigLake, Analytics Hub, BigQuery Omni
✅ AlloyDB & Cloud SQL Enterprise
Plus, the classics (aka the “hits”):
✅ BigQuery, Dataflow, Dataproc, Cloud Storage, and IAM.
✅ Composer, Dataprep, & Datafusion.
✅ Streaming pipelines with Pub/Sub
✅ Cloud Data Loss Prevention, Bigtable architecture, and row key design.
And a sprinkle of networking to top it all off.
Make sure you know the ins and outs of the classics, and brush up on the new things!
Pro Tip: Google Cloud Documentation is your friend.
No more machine learning, machine learning algorithms, neural networks, etc. (although a good data engineer knows the concepts and basics, so it’s up to you if you want to bypass knowing all that — I didn’t).
See this LinkedIn post from Thomas Rocher, who also recently passed. His experience lines up with my own.
My Main Resources Were
Google Cloud Skills Boost — Data Engineer Learning Path
Official Google Cloud Certified Professional Data Engineer Study Guide by Dan Sullivan — This is massively out of date, but I still went through it and found most of the topics held up.
ChatGPT Study Buddy — Used ChatGPT as a study buddy. When I didn’t understand something or needed further context, I’d ask and then dive into the Google documentation to learn for myself.
Google Cloud Documentation —This is a wealth of information, and I cannot overstate how important it is to read through the documentation for things that need more clarity and understanding.
Hands-on experience — If you don’t have a test environment to try things on, you will not understand what you are doing. The best way to learn is to do. I highly recommend building things out yourself in GCP to learn.
Guang Xu’s PDE cheat sheet — This is useful to refresh and solidify your knowledge (although also quite out of date).
Practice Exams — I can’t vouch for any particular practice exam site because, well, they were all sh*t and way out of date, but they gave a good feel for some of the ways the questions would appear. I tried ExamTopics and Skillcertpro. I liked the explanations and group discussions on ExamTopics, but everyone has their two cents about the answers, which can leave you more confused than ever (that’s where ChatGPT came in, and where I would go to the source of truth: the Google Docs).
Awesome GCP Certifications by Satish VJ — I found his Git repository really useful for reading other people’s stories on how they passed the exam.
Final Thoughts
If you’re planning to take this exam, buckle up… It’s tough. The sheer amount of things you need to learn and grasp is daunting.
You will need to spend and invest a lot of time prepping for the exam — there’s no getting around that part. I definitely spent way more time on this exam than I did for the Associate Cloud Engineer Exam. I do like the fact that I now have a solid understanding of the Google ecosystem from a data engineer’s perspective. I have also used what I’ve learned in my day-to-day work, so that in itself is a win.
I hope the advice here somehow helps those taking the exam to feel a little more prepared. Remember, it’s up to YOU and no one else — hard work, perseverance, and determination. Good luck.
📩 Think this is valuable? Share it with someone who might benefit.
🔥 Last Week's Most Read Article 🔥
Thanks for reading! I send this email weekly. If you would like to receive it, join other readers and subscribe below to get my latest articles.
👉 If you enjoyed reading this post, and think this is valuable? Share it with someone who might benefit. Or click the ❤️ button on this post so more people can discover it on Substack 🙏
🚀 Want to get in touch? feel free to find me on LinkedIn.
🎯 Want to read more of my articles, find me on Medium.
✍🏼 Write Content for Art of Data Engineering Publication.