Professional Data Engineer Exam Details
Like other Google exams, this exam also consists of multiple choice and multiple select questions. Consider the fact that you need to pay $200 for the registration. After that, you will access the test for 2 hours which is presented either in English or Japanese. Moreover, you can either take the exam online or have to find a test center near your place to take this test.
There is no formal prerequisite for the exam but it is recommended to have 3-4 years of experience within the data engineering field and to be responsible for the tasks related to data engineering and machine learning. So, on the final test day, you need to have exhaustive knowledge about these domains to perform your best.
- Designing data processing systems
- Providing solution quality
- Operationalizing machine learning models
- Building data processing systems
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Career Path
Completing the exam associated with the Google Professional Data Engineer certification provides you with a great validation of your skills in designing, building, operationalizing, securing, and monitoring data processing systems. The job roles that you can take up after getting certified include a Google Cloud Data Engineer, an Operations Engineer, a Cloud Infrastructure Engineer, a DevOps Infrastructure Engineer, a Cloud Database Engineer, a Google Cloud IAM Engineer, a DataOps Engineer, a Big Data Engineer, a Google Cloud Platform Data Architect, and more. The average salary that you can expect to earn with this certificate is around $125,550 per year. However, the real remuneration will depend on a specific job title, location of an individual, and his/her working experience.
Reference: https://cloud.google.com/certification/data-engineer
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This course is normally taken by data scientists, data analysts, and business analysts who are in the field of Google Сloud. It is a good way to prepare for your final exam because it teaches you all the details including 7 modules that cover all the Professional Data Engineer exam objectives:
- Additional Resources
- Compute and Storage Fundamentals
- Scaling Data Analytics
- Introducing Google Cloud Platform ‘
- Machine Learning
- Data Processing Architectures
- Data Analytics on the Cloud
Google Professional-Data-Engineer Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Designing data processing systems (~30% of the exam) | 30% | - Designing data pipelines
|
| Topic 2: Preparing and using data for analysis (~15% of the exam) | 15% | - Sharing data securely
|
| Topic 3: Maintaining and automating data workloads (~15% of the exam) | 15% | - Monitoring data pipelines and data processes
|
| Topic 4: Ingesting and processing the data (~20% of the exam) | 20% | - Building and maintaining data structures and databases
|
| Topic 5: Storing the data (~20% of the exam) | 20% | - Selecting storage systems
|



