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Google Professional-Data-Engineer

Professional-Data-Engineer

Exam Code: Professional-Data-Engineer

Exam Name: Google Certified Professional Data Engineer Exam

Updated: Aug 16, 2026

Q & A: 433 Questions and Answers

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About Google Professional-Data-Engineer Exam

Prerequisites

There are no formal requirements that the candidates need to meet to qualify for the Google Professional Data Engineer certification. However, without some level of professional experience, it will be difficult for the students to ace the qualifying test. The target individuals are recommended to have three or more years of industry experience, including one or more years of experience in designing and managing solutions with the help of Google Cloud Platform. It is preferable that the applicants also possess some basic database knowledge.

Career Opportunities

The certified individuals can explore a variety of job opportunities. Some of the positions that they can take up include a Software Engineer, a Cloud Architect, a Data Engineer, a Sales Engineer, a Data Scientist, a Cloud Developer, and a Kubernetes Architect, among others. The salary outlook for these job roles is an average of $128,500 per annum.

Exam Overview

The Professional Data Engineer certification exam is a 2-hour test consisting of the multiple-choice and multiple-select questions. The students can take it in the English or Japanese languages. To register for and schedule the exam, you must pay the fee of $200. It is possible to sit for this test in an online proctored format at a remote location. You can also take it as an on-site proctored exam at a designated testing center.

In recent years, many people choose to take Google Professional-Data-Engineer certification exam which can make you get the Google certificate that is the passport to get a better job and get promotions.

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Google Professional-Data-Engineer Exam Syllabus Topics:

TopicDetails
Topic 1
  • Maintaining and automating data workloads: It discusses optimizing resources, automation and repeatability design, and organization of workloads as per business requirements. Lastly, the topic explains monitoring and troubleshooting processes and maintaining awareness of failures.
Topic 2
  • Preparing and using data for analysis: Questions about data for visualization, data sharing, and assessment of data may appear.
Topic 3
  • Ingesting and processing the data: The topic discusses planning of the data pipelines, building the pipelines, acquisition and import of data, and deploying and operationalizing the pipelines.
Topic 4
  • Storing the data: This topic explains how to select storage systems and how to plan using a data warehouse. Additionally, it discusses how to design for a data mesh.
Topic 5
  • Designing data processing systems: It delves into designing for security and compliance, reliability and fidelity, flexibility and portability, and data migrations.

Reference: https://cloud.google.com/certification/data-engineer

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