Data Engineering on Google Cloud Platform: How to Get Certified

Ready to take your data engineering career to the next level? This guide is your one-stop shop to getting certified as a data engineer on Google Cloud Platform.

Google Cloud Platform

Despite the global pandemic, big data has been among the handful of industries that saw growth and is expected to expand significantly in the coming years.

Occupying a leadership position in the $70 billion market is Google Cloud Platform (GCP), garnering “interest in big data analytics and analytics workloads.” As organizations proactively leverage data and analytics in their decision-making, opportunities in the field are projected to grow—there are over 80,000 open jobs listed on LinkedIn in data engineering in the US alone, across leading organizations like Apple, Nestle, PayPal, etc. Salaries reflect this demand too. 

To compete in this rapidly evolving market and command top salaries, you need more than just skills and experience. You need certifications that can demonstrate your worth.

In this blog post, we discuss the advantage that a GCP data engineer certification can offer. We also explore commonly asked questions and offer advice on how you can get your certification quickly.

What Is the Google Cloud Platform Data Engineer Certification?

Google Cloud offers one associate-level certification and eight professional certifications across cloud architecture, security, DevOps, and machine learning. The data engineer certification is one of the most sought-after among big data and analytics professionals.

3 Reason You Should Get Certified as a GCP Data Engineer

In the 2020 Global Knowledge Study, over half of the respondents said the quality of their work improved, one-third found their work more engaging, and 15% say they make fewer errors, post-certification. Beyond the improvement in their ability to do work itself, there are several other benefits too. 

1: GCP certification increases chances of getting hired

Certifications play a crucial role in demonstrating to potential employers that you’re skilled. It is common in most job descriptions for data engineer roles to expect an active certificate. Take this GCP data engineer role at Diverse Lynx, CA, for instance, where “GCP Professional certification is highly desirable.” Or this role at Accenture, where a “certificate is a plus,” even if you have a wide range of skills and experiences.

2: GCP certification helps you negotiate better salaries

The Google Cloud Data Engineer certification stands third among the top-paying certifications worldwide. Certified Google Cloud engineers command an average salary of $114,636 but often earn a lot more. 

3: GCP certification improves growth opportunities

Certifications regularly catalyze careers, empowering them to grow within their organization to leadership positions or move to more challenging careers. 8% of those surveyed said they received promotions on completing a certification. 16% either got new jobs or plan to make the switch soon. 

Can You Get Certified as a GCP Data Engineer if You Don’t Have a Degree?

Yes. The Google Cloud Data Engineer certification demands no prerequisites from candidates wishing to take the exam. It doesn’t require you to have any other formal qualification either. It does recommend 3+ years of industry experience with a year in GCP technologies, but you are allowed to take it without that too.

Google Cloud Professional Data Engineer Exam

3 Tips to Prepare You for the Google Cloud Data Engineer Exam

In order to be successful in the GCP data engineer certification exam, you will need to understand the concepts you’ll be tested on, gain hands-on experience, and take practice exams.

Tip 1: Understand the concepts you’ll be tested on

Google Cloud offers a clear exam guide outlining all the concepts and practices you’ll be tested on. The curriculum is structured under four sections: Designing data processing systems, building and operationalizing data processing systems, operationalizing machine learning models, and ensuring solution quality.

Under each of these, there are specific technologies that are listed. Spend time learning them thoroughly. Begin with Google’s resources, including the learning path, webinars, and other documentation. But don’t stop there. Seek other external resources for a deeper understanding. The Springboard Data Engineering Bootcamp is designed to teach all these and more.

Tip 2: Gain hands-on experience

Remember that The Google Cloud Data Engineer certification is a practitioner’s exam. It requires you to have practical knowledge and experience in the tech. If you already work on GCP, you might be able to run trial workloads as part of your job. If not, you can use the free tier on GCP to set up a sandbox and practice your skills.

Tip 3: Take practice exams

There are several resources available that can help you get a view of how the exam is conducted. Google itself offers sample questions that you can use to prepare. Spend time testing yourself on various sets of questions before you schedule your exam. 

What Should You Expect in the GCP Data Engineer Exam?

The GCP Data Engineer certification is a two-hour-long exam that you can take remotely or in person at a test center. It includes multiple-choice or multiple-select questions, in both English and Japanese. Major topics covered are:

  • Data storage, data analytics, machine learning, and data processing
  • Products such as BigQuery, Apache Hadoop, cloud data flow, TensorFlow, stackdriver, etc.
  • Use cases, best practices, and case studies from various Google projects

Where Can You Practice for the GCP Data Engineer Exam?

Start with the Google sample exams. But don’t restrict yourself to just those. Look at exams from the past few years and learn what has changed. There are several other free and paid resources you can use such as Whizlabs, Pluralsight, etc. Choose ones that are right for you—and good luck!

Ready to switch careers to data engineering?

Data engineering is currently one of tech’s fastest-growing sectors. Data engineers enjoy high job satisfaction, varied creative challenges, and a chance to work with ever-evolving technologies. Springboard now offers a comprehensive data engineering bootcamp.

You’ll work with a one-on-one mentor to learn key aspects of data engineering, including designing, building, and maintaining scalable data pipelines, working with the ETL framework, and learning key data engineering tools like MapReduce, Apache Hadoop, and Spark. You’ll also complete two capstone projects focused on real-world data engineering problems that you can showcase in job interviews.

Check out Springboard's Data Engineering Career Track to see if you qualify.

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