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Google Professional Data Engineer Certified Professional salary

The average salary of a Google Professional Data Engineer Certified Expert in

• England - 115,632 POUND
• Europe - 135,347 EURO
• India - 25,42,327 INR
• United State - 151,247 USD

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.

Data Engineering on Google Cloud course

It is a 4-day course that gives hands-on experience to the candidates and allows them to build data processing systems on Google Cloud. It will also show you how to design data processing systems, analyze data and build end-to-end data pipelines and machine learning. In order to get a better understanding of the course, you need to complete the big data machine learning course or get equivalent experience. This course also aids you in developing applications using a programming language such as Python and covers the following objective:

• Influencing unstructured data using ML APIs on Cloud Dataproc
• Processing batch and streaming data by using autoscaling data pipelines on Cloud Dataflow
• Predicting machine models using TensorFlow and Cloud ML
• Designing and building data processing systems on the Google Cloud Platform
• Enable insights from streaming data

Target Audience

The candidates for this certification are the data engineers or those aiming to become one. These individuals should have the capacity to allow data-driven decision-making through the collection, transformation, and publishing of data. They have the expertise in designing, building, and operationalizing secure data processing systems and monitoring the same. This is with the specific emphasis on compliance and security, fidelity and reliability, portability and flexibility, as well as efficiency and scalability.

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

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