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How I Conquered Google Cloud's Toughest Certification: My Journey to Becoming a Google Cloud Professional Data Engineer (2025 Edition)
Anil Kumar | Gen AI Architect | Developer | Manager | Holder of All 13x GCP Certifications
🔗 Medium Blog | LinkedIn
Overview
On 27 May 2025 at 4:30 AM IST, I took what I consider the most challenging of all Google Cloud certifications — the Google Cloud Professional Data Engineer (PDE) exam. With limited preparation time and a packed schedule, I had to strategize efficiently.
Despite the pressure, I passed.
In this article, I’ll share:
The real exam experience
Key topics you must focus on
A time-efficient preparation strategy
And how I maintained confidence throughout the process
Exam Info & Official Resources
📌 What the Exam Focused On
Based on my experience, the questions were heavily scenario-based, demanding deep understanding of GCP services, architecture patterns, and data engineering best practices.
Here are the most important topics:
High-Frequency Topics:
Pub/Sub → Dataflow → BigQuery Pipelines
BigQuery (expect multiple, in-depth questions)
Dataprep & Datastream
BigLake, Dataplex, Datafusion
Cloud SQL, Spanner, Datastore, Memorystore – Understand use cases and trade-offs
Data Lake vs Data Mesh – Conceptual clarity is key
BigQuery ML & Feature Engineering – Few but tricky questions
My Fast-Track Preparation Strategy
With a demanding schedule, I followed a two-pronged strategy focused on depth, not breadth:
1. Skill Boost Learning Path
I completed the official Data Engineer path on Google Cloud Skill Boost.
This helped reinforce foundational concepts and introduced newer services recently added to the exam.
2. Practice with Realistic Mock Exams
To simulate the pressure and difficulty of the exam, I used this full-length mock test on Udemy:
🔗 GCP Data Engineer Practice Test
You can also check for community coupons regularly posted here:
🔗 CertShield Free GCP Coupons
My Personal Experience
This exam was the most mentally demanding of all my GCP certifications.
The questions were long, with subtle differences between answer choices.
BigQuery ML and pipeline optimization questions really tested both data and ML knowledge.
Time management and reading comprehension were as important as technical skills.
🏁 Outcome
I passed the Google Cloud Professional Data Engineer Certification ✅
This marks the completion of all 13 GCP certifications in my journey.
Final Advice for Aspirants
Understand architectural decision-making, not just definitions.
Spend focused time on BigQuery, Dataflow, and Dataplex.
Mock exams help immensely—they train your brain for GCP’s questioning style.
Keep pace with new services like BigLake and Datastream, which are showing up in recent exams.
About Me
👋 I’m Anil Kumar, a Gen AI Architect and Cloud Specialist.
With all 13 GCP certifications under my belt, I actively mentor, build, and give back to the tech community.
Feel free to connect or follow my GCP content journey:
💡 “Certifications are not just badges—they are milestones in a journey of continuous learning.”
Feel free to drop questions or share your prep journey in the comments! 👇
