Jinal Desai

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.   – Google

Google Cloud Professional Data Engineers are currently high in demand for their ability to maintain the process of accumulating, converting, and publishing data with a certain level of expertise.

For this exam, I will recommend to have a strong experience in Google cloud with various data focused services. If you don’t have strong experience and still targeting for this certification, no worries. This article is for everybody who is aspiring for the certificate.

What Google expects from you in this certification exam is, “Demonstrate your proficiency to design and build data processing systems and create machine learning models on Google Cloud Platform.”

Before you start going through the links I’ve compiled in this article, just scan through this link to understand various topics covered as part of the certification exam.

If you prefer video courses for learning, I’ll suggest following courses.

Video Courses and Labs

• Coursera
• Acloudguru
• Udemy
• Cloudacademy
• Qwiklabs
  • • Baseline: Data, ML, AI
    • Data Engineering
    • Data Science on Google Cloud
    • BigQuery Basics for Data Analysts
    • Engineer Data in Google Cloud
    • Scientific Data Processing
    • Build and Optimize Data Warehouses with BigQuery
    • BigQuery for Data Warehousing
    • Building Advanced Codeless Pipelines on Cloud Data Fusion
    • Insights from Data with BigQuery
    • BigQuery for Data Analysis
    • Data Catalog Fundamentals
    • Building Codeless Pipelines on Cloud Data Fusion
    • BigQuery for Marketing Analysts
    • Cloud SQL
    • BigQuery for Machine Learning

If you prefer the reading way, you can go through following links. I’ll recommended to learn few topics through reading and practicals, mere video training won’t help much.

Reading

First of all, I’ll recommend to go through the Data Dossier prepared by Matthew and is freely available online. Second step is to learn SQL skills thoroughly with deep understanding of advanced query mechanism using SQL language. You can also do crash course freely provided by Google, “Crash Course in Machine Learning“.

Few more links by topics.

Practice Tests

After the preparation is done, just go through few practice tests.

• Google
• Examtopics
• Testprep