How to pass the Google Cloud Professional Data Engineer Exam

This video covers the most recent exam syllabus. Maybe you had googled the above title, but no worries you have arrived on the best video that will guide you through this journey.

These Data is a rare commodity and ability to manage it is much needed with an increased need for Data Engineers by companies that own a lot of data in Exabytes, Zettabytes and Yottabytes, to help implement business decisions.

In this guide, I will visualize an idea on what the exam should look like and how to get prepared for success.

My Background

Having graduated with a Master’s degree in Computer and Information Science in USA, I spent some years working in the Data Analytics career path. This was the first time I was exposed to the role of a Data Engineer and the Google Cloud Platform.

One of the technical solutions to the business requirement was using Big Query as our serverless data warehouse to enable scalable analysis over petabytes of data, also supporting fast querying of nested rows using the familiar standard SQL syntax. Furthermore, allowing simple integration with other Google Cloud products such as Data Studio for analytical reports and AI platform for Machine Learning.

As at the time I was very curious to know job responsibilities of a Data Engineer. Data Engineers provision and set up data platform technologies that are on-premises and in the cloud. They also manage and secure the flow of structured and unstructured data from multiple sources. So mostly building Data pipelines and making data accessible for analysts that query/manipulate data.


  1. Linux Academy

Course: Google Cloud Certified Professional Data Engineer
Cost: $49/month (1 week free trial)

Helpfulness: 9/10

This course is very helpful and covers about 70% of the content that came up in the exam. This course also offers a combination of presentations, hands-on labs and demos.

This course provides a high-level overview of each Google Cloud service and covers key concepts as well as Google’s best practices for utilizing each one.

The course was well structured, beginning from foundational concepts, to the different types of databases, architecting pipelines, machine learning and data visualization.

There are a variety of hands-on labs, walkthroughs and quizzes that help consolidate your understanding and provide an opportunity to test the material you’ve learnt in the videos directly on the Google Cloud Platform.

I recommend taking this course first if you’re new to Data Engineering as it is a bit easier to understand than the Coursera course.

If I were to recommend just one paid subscription, this would be the one. Paying for a monthly subscription is worth the price. Not only do you get access to the amazing resources on the GCP course, but you’ll also have full access to all other courses offered by Linux Academy (which I used).

Just a side note, Linux Academy will be launching a platform called – A Cloud Guru, but will retain its presence and updated training on its Linux Academy platform.

2. Coursera

Course:Data Engineering with GCP Professional Certificate
Cost:$49/month (1-week free trial)
Helpfulness: 7/10

Coursera as an online MOOC, offer a combination of presentations, hands-on labs and demos. I found this course to be quite advanced for someone without any prior commercial experience. I wasn’t aware of current technologies such as those in the Hadoop ecosystem and was overwhelmed with many unfamiliar terminologies.

However, I highly recommend takingthe Preparing for the Google Cloud Professional Data Engineer Exam Courseabout a week or two before taking the examination. This is like the revision lecture at university, where they did a quick overview of the key scenarios you expect to see in an exam.

3. Cloud Academy

Course: Google Data Engineer Exam — Professional Certification Preparation
Cost: $49/month (1-week free trial)
Helpfulness: 8/10

The most useful part of this course was, it covered topics such as Security and Networking, Data Encryption and Compute Engines which were not covered in the other courses, but can be tested according to the official exam syllabus.

I found the hands-on labs a bit harder and more copy-pasting long lines of pre-written commands.

Some other areas, I recommend you should study or look out for videos are:

  • Big Query ML
  • Cloud Key Management & Data Encryption
  • Kafka
  • Failover replica

Study Strategy

We all have different study patterns and approach to visual learning. I will recommend choosing what works best for you.

Hands-on practice

Not having experience using the Google Cloud Platform, I recommend you practice with the hands-on labs and Qwiklabs. I recommend you do not memorize how to get each task done, but implement as an opportunity to familiarize yourself with the service and the overall GCP environment.

With Linux Academy subscription, you get access to the cloud sandbox where you can receive guest user credentials to use GCP for 3 hours per session.

You can still gain valuable practice without breaking your wallet by using this cloud sandbox or by creating a free GCP account ($300 free credits) and following the task instructions for the hands-on labs on Coursera or Qwiklabs. (On Qwiklabs, you are essentially paying to use the GCP environment for a fixed time).

I highly recommend you practice the Hands-on Labs, read the official Google Cloud Documentation — though unrealistic to read the whole documentation but my I recommend you read the documentation for the topics covered in the online videos also try as many times practice questions before the official exam. Most important part of the practice questions of your revision is to make a note of all the questions you failed and review them again once more.

Here are some extra free practice questions:


The exam consists of 50 questions and you have 2 hours to complete exam.

Registration fee is $200. There is a bookmark feature where you can bookmark questions for later review.

Preferably, i would say the exam is about 20% – 25% harder than the practice exam/practice questions. Many of the questions can cause a lot of self doubt such as the cost vs performance trade-off.

My advice is to pace yourself and don’t waste time on a question. If you do not know the answer or unsure about your answer, bookmark it and move on to the next question.

I will advice you do not panic if you are unable, to answer all questions your first time. I had a hitch on the first few questions and then bookmarked few questions for later review.

Finally, great to see you made it this far reading this article. I believe this article have been helpful and provided confidence for you in getting prepared for this exam.

You can pass this exam without industry experience and prepare for it from a basic knowledge on cloud concepts.

When you complete the exam, you will only receive a Pass or Fail result.

Subscribe to this blog for free future email updates on Data Science articles.

Please follow and like us:

Leave a Reply

Your email address will not be published. Required fields are marked *