Google has established a path for IT professionals endorse as a Data Engineer on the GCP platform. This accreditation program gives Google Cloud professionals a way to endorse their skills. The evaluation relies on a meticulous exam using industry-standard methodology to conclude whether or not an aspirant meets Google’s proficiency standards.
The Professional Data Engineer exam assesses your ability to:
Google Professional Data Engineer Exam certification is evidence of your skills, and expertise in those areas in which you like to work. If a candidate wants to work as a Google Professional Data Engineer and prove his knowledge, Certification is offered by Google. This Google Professional Data Engineer Certification helps a candidate to validate his skills in Big Data and Data Engineering Technology.
The registration for the Google Professional Data Engineer Exam follows the steps given below.
The average salary of a Google Professional Data Engineer Certified Expert in
Individuals should pursue the exam if they want to demonstrate their expertise and ability to design and develop Data Engineering. Following professional get benefited from Google Professional Data Engineer Certification
The Google Professional Data Engineer Certification is one of the highest level of certification mainly focussing to the professional Data Engineering.
There is no prerequisite for this exam but still it would be best to follow some sequence in order to prove immense knowledge as a Google professional Data Engineer.
You can complete Google Associate Certifications then approach for the professional certification. For more information related to Google cloud certification track
A Professional Data Engineer enables data-driven decision making by collecting, transforming, and publishing data. A data engineer should be able to design, build, operationalize, secure, and monitor data processing systems with a particular emphasis on security and compliance; scalability and efficiency; reliability and fidelity; and flexibility and portability. A data engineer should also be able to leverage, deploy, and continuously train pre-existing machine learning models.