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The Google Cloud Certified Professional Data Engineer certification validates your ability to design and build data processing systems on Google Cloud, one of the most respected data credentials in the industry. The Google Cloud Certified Professional Data Engineer exam checks whether you can actually design, build, and operationalize a real data pipeline, not just recognize BigQuery in a list of GCP services.
The Whizlabs Google Cloud Certified Professional Data Engineer course covers designing and building data processing systems on Google Cloud, from foundational concepts through to hands-on pipeline work. You'll work through structured video lessons and exam-style practice questions that mirror the real Data Engineer exam, building the practical judgment needed to apply these skills on the job.
By the end of this Google Cloud Certified Professional Data Engineer course, you'll be ready to sit the Data Engineer exam and earn the credential. This Google Cloud Certified Professional Data Engineer training pairs guided lessons with a full Google Cloud Certified Professional Data Engineer practice test, so you walk into the Data Engineer exam fully prepared for how Google frames these data engineering scenarios.
24x7 support from Google-certified experts
This course is valid for 2 years from the date of purchase.
Practice tests with unique, exam-style questions
Detailed explanations for every practice question
Hands-on labs using real Google services
Downloadable Data Engineer cheat sheet for quick revision
The Data Engineer exam is organized around the core data engineering lifecycle this Google Cloud Certified Professional Data Engineer course is built to cover.
Designing Data Processing Systems. Choose the right storage, processing, and pipeline architecture for a given business need.
Building and Operationalizing Data Processing Systems. Build, deploy, and maintain reliable data pipelines using GCP tools like Dataflow, BigQuery, and Pub/Sub.
Operationalizing Machine Learning Models. Deploy and monitor ML models within larger data pipelines on GCP.
Ensuring Solution Quality.
The Google Cloud Certified Professional Data Engineer course lays out a clear path to the Data Engineer exam, so you're not guessing what to study next.
Start with the video lessons in this Data Engineer course to build a working model of data pipeline design, processing, and ML operationalization on Google Cloud. Then use the hands-on labs in the Google Cloud Certified Professional Data Engineer course to actually build pipelines using Dataflow, BigQuery, and Pub/Sub, rather than only reading about them.
Next, work through the Data Engineer practice test set. Each Google Cloud Certified Professional Data Engineer practice test question comes with a detailed explanation, so a wrong pick becomes a lesson you retain rather than a gap you carry into exam day.
When your Data Engineer practice test scores stay consistently strong, you're ready to book the Google Cloud Certified Professional Data Engineer exam. Finish this Data Engineer course end to end, and you'll sit the exam already comfortable with how Google frames these data engineering scenarios.
The Data Engineer certification is a professional-level credential, so there's no mandatory prior Google Cloud certification, though many candidates come in with the Google Cloud Certified Associate Cloud Engineer already under their belt.
Once you pass, the Google Cloud Certified Professional Data Engineer certification stays valid for 3 years. Before it expires, you can renew the Data Engineer certification by retaking the current exam.
Many data professionals pair the Google Cloud Certified Professional Data Engineer certification with the Google Cloud Certified Professional Cloud Architect to combine deep data engineering skills with broader cloud architecture expertise across GCP.
This certification validates your ability to work with designing and building data processing systems on Google Cloud. It signals to employers that you can apply these skills in real Google projects, supporting stronger roles, responsibilities, and career growth.
Positions you for data engineers and analytics engineers roles, and signals proven, job-ready expertise in designing and building data processing systems on Google Cloud.
Helps your organization apply designing and building data processing systems on Google Cloud more effectively, reducing risk and improving efficiency in real deployments.
Deepens your hands-on understanding of designing and building data processing systems on Google Cloud, moving beyond theory into practical, job-ready skills.
Professional-level certifications like this are consistently linked to stronger salaries and career growth in Google-related roles.
Exam Format and Information
Prior Certification
Not Required
Exam Validity
3 Years
Exam Fee
200 USD
Exam Duration
120 Minutes
No. of Questions
50-60 Qs
Passing Score
Pass/Fail
Best for those with hands-on or working familiarity with designing and building data processing systems on Google Cloud.
English and Japanese.
Multiple choice and multiple select questions.
There are no formal prerequisites for this exam. Hands-on experience with designing and building data processing systems on Google Cloud makes it more approachable. It's designed for data engineers, analytics engineers, and anyone building these skills.
Data engineers working with designing and building data processing.
Analytics engineers preparing for professional-level certification.
IT professionals expanding into this specialization.
Consultants advising clients on Google best practices.
Students and career changers entering the field.
Anyone pursuing the Data Engineer credential.
In this training, you will get unlimited access to 3 practice tests with 50 unique questions, 1 practice test with 31 unique questions, and one free test with 20 questions. All these questions are similar to the actual exam questions and can be treated as mock exams. Practice for the actual certification exam by taking up the free test first followed by the Video Course and attempt all the 4 practice tests included in this training.
Get help from Google-certified trainers whenever you're stuck on a concept or question.
Practice with real Google services in guided labs that mirror the exam and the job.
Unique Data Engineer style questions with detailed explanations from subject matter experts.
Explore live Google services in a ready-to-use sandbox environment.
Testimonials
Overall Feedbacks
Big Query is the serverless, cost-effective, and highly scalable cloud data warehouse that is designed to enable users to make informed decisions quickly and transform the business data with ease. The significance of using Big Query in GCP are:
To run analytics at scale efficiently than cloud data warehouse alternatives
To analyze gigabytes to petabytes of data quickly using ANSI SQL at the fastest speeds
To democratize insights seamlessly with a trusted and more secure platform to scale your needs
As more organizations rely on designing and building data processing systems on Google Cloud, they need certified professionals who can apply these skills correctly, which drives strong demand for Google Cloud Certified Professional Data Engineer holders.
No formal prerequisite is required for most candidates, though hands-on experience with GCP data tools makes the Google Cloud Certified Professional Data Engineer course considerably easier to work through.
Yes, our practice tests consist of different types of questions as per the real exam format. As the Google Cloud Certified Professional Data Engineer exam may contain case studies with multiple questions, we also provide case study type questions in our practice tests.
Yes, even if you are a non-technical person, you can become a Google Cloud Professional Data Engineer. The recommended requirement to take up the Google Data Engineer certification exam is to have significant knowledge of cloud services and Google Cloud Platform with considerable experience. It is good if the candidate has a minimum of 12 months of hands-on experience with Google Cloud Platform. But, even if you are a fresher or have a non-technical background, you can take some training to get familiar with Google Cloud Platform.
Also, you can get hands-on with the Google Cloud Platform by using Google Cloud free tier account. After gaining some experience of working with the GCP platform, you can validate your skills with the GCP Data Engineer certification exam to become a Google Cloud Professional Data Engineer.
Through structured video content, unlimited practice test attempts, hands-on labs, and expert support from Google-certified trainers if you get stuck.
At Whizlabs, we are committed to building high-quality training courses and practice tests for the Google Cloud Professional Data Engineer certification exam.
While a training course helps you learn various concepts and get ready for the exam, practice tests check your preparation level. Thus, you get to know about your weak areas and can work on them to improve.
If you come across any doubts while taking the Google Data Engineer certification practice test and online course, our experts help you to clear them and thus you become more confident to pass the real exam. So, we highly recommend you to go through our Google Cloud Certified Data Engineer practice exam before sitting in the actual exam.
Every question on the Data Engineer exam maps back to one of these areas, so the Google Cloud Certified Professional Data Engineer exam rewards the ability to run a complete, production-grade data pipeline, not just query a dataset once and stop.
4.9/5
4.8/5
julián alvarez
julián alvarez
