Pass The Google Cloud Professional Data Engineer Exam (2024)
As a seasoned Data Engineer with a passion for cloud-native technologies, I’ve always been drawn to the innovative solutions offered by Google Cloud Platform (GCP). My journey toward becoming a Google Cloud Professional Certified began eight months ago when I successfully passed the Google Cloud Professional Cloud Architect certification. Building on this foundation, I recently achieved another significant milestone by passing the Google Cloud Professional Data Engineer certification.
My experience as a Google Cloud Professional Cloud Architect provided me with a solid understanding of designing and building scalable, reliable, and cost-effective cloud solutions. This knowledge served as a valuable base as I embarked on my journey to become a Data Engineer.
Becoming a Google Cloud Professional Data Engineer isn’t just about passing the exam — it’s about gaining the expertise to master Google Cloud technologies for data ingestion, data processing, data warehousing, and data analysis. The Google Cloud Professional Data Engineer Exam challenges my ability to design, implement, and maintain data processing systems on GCP.
Preparation
While my Cloud Architect background gave me a head start, I still needed to dedicate significant time and effort to prepare for the Professional Data Engineer certification. The first step in my preparation was to create a comprehensive study plan. I carefully reviewed the exam objectives and identified the key areas I needed to focus on.
Here are some tips you can follow for passing the exam. And I also used the same tips for passing my Cloud Architect exam.
- Learn the exam guide to check the required topic that you are going to cover for your preparation.
- Training with Google Cloud Skills Boost. Complete the Professional Data Engineer Learning Path (at no cost for 30 days for new users), including the hands-on labs, quests, and courses. It’s not a requirement to go through each step in the Learning Path before you take the exam, but the more you know, the better prepared you’ll be!
- Keep doing self-assessment by doing as many practice tests. Google provides a free practice test. You can attempt it and review your understanding. If you score more than 70–80% on the first attempt then focus on the area where you need more clarity.
By combining the questions from the three resources above, you’ll be preparing with many practice questions, which should be more than enough to get you ready for the exam. If you still don’t feel confident enough to take the exam, there are additional resources with more practice questions, such as: IT Exams and Exam Topics.
But, not all answers provided are correct. You’ll need to verify and find the right answers yourself. However, a great feature of the platform is the ability to view comments and answers from others who have worked on the same questions. You can also contribute by sharing your insights and discussing which answer best fits each question.
Passing The Exam
This Professional Data Engineer is also similar with other Professional Certifications exams which are just as much about technical knowledge as they are also about critical thinking. It mean you will not know the right ‘correct’ answer for many questions, but you might know the ‘wrong’ answers. The test requires process of elimination. There are often two obviously wrong answers and then a toss-up between the two remaining answers. When you face a question that does have an obvious answer, make sure to read the other questions to see if there are any obvious candidates for elimination.
The exam consists of 50 multiple choice questions within 2 hours and cover these following broad areas:
- Designing data processing systems (approximately 22%).
- Ingesting and processing data (approximately 25%).
- Storing data (approximately 20%).
- Preparing and using data for analysis (approximately 15%).
- Maintaining and automating data workloads (approximately 18%).
Within each of these areas, you may encounter questions related to:
- Data ingestion: Dataflow, Pub/Sub, Cloud Storage.
- Data processing: Dataproc, Data Fusion.
- Data warehousing: BigQuery.
- Data analytics: Looker.
- Data governance and security: Data Loss Prevention, Cloud Identity and Access Management.
Understanding these topics is crucial for passing the exam and demonstrating your expertise in data engineering on the Google Cloud Platform. By focusing on these areas and actively engaging with the exam objectives, you’ll be well-prepared to demonstrate your proficiency in data engineering on the Google Cloud Platform and achieve your certification goals.
Conclusion
My journey to obtain these certifications has been incredibly rewarding. Obtaining both the Google Cloud Professional Cloud Architect and Data Engineer certifications has been a significant accomplishment. It has validated my skills, expanded my knowledge, and opened up new opportunities. I encourage anyone who is passionate about cloud computing and data engineering to pursue these certifications.
Don’t be afraid to challenge yourself and step outside your comfort zone. The effort you put into studying and preparing for these certifications will be well worth it. The skills you acquire will be in high demand, and you’ll be well-positioned to succeed in the dynamic world of cloud computing.
