Google-Professional-Data-Engineer-A-Complete-Guide

Google Professional Data Engineer – A Complete Guide

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A data engineer should possess the skills to design, build, secure, monitor, and operationalize data processing systems. With such a skill set, you can collect, transform and publish data for the sake of the productivity of an organization. Google Professional Data Engineer certification enables an individual to make decisions for an organization based upon data.

Along with clearing this certification, the data engineers need to put special emphasis on scalability, efficiency, security compliance, flexibility, portability, and reliability aspects. Along with that, the data engineer is also responsible for leveraging and deploying the machine learning models and training them on a continuous basis.

This is a complete guide specified for helping you clear the Google Professional Data Engineer examination. In this guide, you will get an idea of the exam overview, detailed topics, stepwise preparation strategy, tips, and salary information, associated with the Google Professional Data Engineer examination and career prospects.

Why go for Google Professional Data Engineer Certification?

Google has put up a dedicated certification for IT professionals who intend to be data engineers over the Google Cloud Platform. It is crucial for you to go with the Professional Data Engineer certification because data analytics and big data analytics are considered the lifeline of any organization or business. Therefore, it is important for individuals to master this technology to take up data-oriented initiatives for helping the business thrive.

For successfully implementing the big data or data initiatives, you will need more proficient skills than being a data analyst or data scientist. You will initially need the skills of a data architect who will be designing the entire framework of data management for your organization. Following that, you will need data engineers to build that designed framework and bring the data pipelines into action for deriving business value out of collected data.

Therefore, if you are willing to pursue your career in the field of data management and optimization, then this certification is a good supportive qualification for you. Getting an edge with this profession demands ideal certification, and Google Professional Data Engineer is an ideal pick for you.

While preparing for this certification, you will gain your skills of using the right tools from the open-source ecosystem of big data. Along with that, you also need to have theoretical and practical knowledge of Python, Scala, or Java to clear this examination with good grades and on the first attempt.

Exam Overview of Google Professional Data Engineer Certification

Google Professional Data Engineer certification intends to help you master the skills of utilizing data for the betterment of an organization. When you have proficiency in designing, building, optimizing, and monitoring data, you can help make important decisions for the business’s productivity. The role of a Data engineer is quite essential as of today for almost every organization. It is because, need for data is quite important for achieving stable growth in business operations. Therefore, this certification is of utmost concern for data engineer aspirants.

This certification exam is for 2 hours and is available for candidates to appear in English and Japanese only. The exam questions are in MCQ format, which will have multiple options for every question. The candidates can prefer to take it either remotely or at any physical test centers, based on personal preference.

If you prefer to take the online examination option, you will have a proctor sharing screen with you to monitor you for the 2 hours of examination. You need to check on the online test requirements specified by Google Cloud before you can opt for this mode of delivering the exam.

If you are not confident about taking an online examination, you can prefer to take the examination at physical centers on-site. You will have a proctor in this exam mode as well to conduct the examination for you. For that, you need to select your nearest test center from the available options over Google Cloud. You can do it while you are registering for the certification exam.

The registration fee for the Google Professional Data Engineer certification is $200. The tax is additional, depending upon the applicable areas. There are no mandatory prerequisites for this certification exam. But, you are advised to have at least three years of industrial experience in handling data management operations and at least one year of experience in designing & managing the solutions with the use of Google Cloud Platform services.

Also Read: FREE Google Cloud Professional Data Engineer Exam Questions

Google Professional Data Engineer Exam Objectives

For clearing the certification exam, you need to be aware of the important areas to consider while you prepare. This certification is going to test your abilities in the areas such as:

  1. Designing Data Processing Systems
  • Selection of the appropriate storage technologies.
  • Designing of the data pipelines.
  • Designing a data processing solution.
  • Migrating data processing and data warehousing
  1. Building & Operationalizing Data Processing Systems
  • Building & Operationalizing storage systems
  • Building & Operationalizing pipelines. (Data cleansing, transformation, batch & streaming, data acquisition, etc.)
  • Building & Operationalizing processing infrastructure. (Provisioning resources, adjusting pipelines, monitoring pipelines, etc.)
  1. Operationalizing Machine Learning Models
  • Leveraging pre-built ML models as a service.
  • Deploying Machine Learning Pipeline.
  • Selecting the appropriate training & serving infrastructure.
  • Measuring, monitoring & troubleshooting the ML models.
  1. Ensuring Solution Quality
  • Designing for Security & Compliance.
  • Ensuring Scalability & Efficiency
  • Ensuring Reliability & Fidelity
  • Ensuring Flexibility & Portability.

These are the areas in which you need to direct your preparation strategies. Moreover, these are the topics on which the certification exam will be based so as to test your skills. Therefore, make sure you put up your efforts towards adapting the right learning methods in order to get your concepts clear and take on the examination confidently.

Step-by-Step Preparation for Google Professional Data Engineer Certification

Ideal preparation is quite important for you to understand and implement the right knowledge onto the exam questions. Becoming a data engineer is not an easy task in this competitive arena. There are immense job opportunities associated with data engineer qualification waiting for you to go with. But, the competition is also immense in the path of getting a job as a data engineer in top companies. Therefore, the key is to obtain the Google Professional Data Engineer certification in one attempt, with an ample amount of practical knowledge. Here’re the steps you should follow to become a Google Certified professional data engineer on the first attempt.

  1. Go Through the Exam Guide

It is important for you to explore the exam guide on priority. It is because you need to understand what this certification intends to offer you the required knowledge and what skills it demands from you. You need to check whether the existing skills you possess are sufficient enough for the GCP data engineer certification or not. If you lack certain skills, then it is time for you to implement superior preparations to adopt the necessary knowledge and expertise for clearing this certification exam.

You will get all of this information from the official exam guide proposed by Google Cloud. The exam follows a blueprint of the syllabus, important topics, and focused elements of considerations. Moreover, understanding that blueprint is important for you to ensure that this is the certification you were looking for in order to approach further with the preparation ideologies.


  1. Take up the Official Learning Path Courses Offered by Google Cloud

The next step of preparation is to take up the learning path courses, available officially over the Google Cloud Platform. This learning path intends to help a candidate cover all the important topics and areas of interest to clear the certification examination on the first attempt.

In the data engineer learning path, you have courses and skill badges to complete that includes:

  • Big Data and Machine Learning Fundamentals- Course
  • Data Engineering on Google Cloud Platform- Course
  • Preparing for the Professional Data Engineering Examination- Course
  • Create & Manage Cloud Resources- Skill Badge
  • Perform Functional Data Machine Learning, and AI Tasks in Google Cloud- Skill Badge
  • Engineer Data with Google Cloud- Skill Badge

Apart from the courses and skill badges, you also get to explore your skills in over 31 labs. Hence, it will help you with efficient preparation aspects for not just clearing the examination but also mastering the proficient skills.

  1. Take Instructor-led Training or Webinars by GCP for In-depth Preparation

You can prefer taking instructor-led training for Google Professional Data Engineer certification. If you are not confident about clearing the fundamentals of this certification through the free modules offered by the GCP learning path, then you can definitely go for the paid training course. You can clear your doubts, get real-time help with practical solutions, and more clarity on select concepts.

To increase the weightage of your preparation, you can take Webinars offered by Google Cloud on-demand. Sign-up to your Google Cloud account, and click on the ‘Watch on-demand’ tab. You will get to attend an informative webinar carried out by Google experts and certified data engineers. They will guide you with important tips and tricks to master the fundamentals of this certification and clear the examination.

Get a detailed understanding of the concepts and critical components of Google Cloud Platform by exploring the Google Cloud Documentations. You can also enroll in the online course for the Google Professional Data Engineer certification.

  1. Solve the Sample Questions and Get Hands-on Practice

You can go to the sample question section of Google Cloud to explore the sample papers of the Data Engineer certification exam. It will give you clarity on how the exam questions are put up and will make you aware of the complexities. These example papers are helpful to guide you with the right intensity of preparation that you must implement. Furthermore, it helps you know your levels, depending upon which you can improve your preparation habits.

Apart from that, you can also get hands-on practice by using Google Qwiklabs. It will help you get your hands upon the Google Cloud technologies. You need to start with the GCP service essentials before moving onto the Data Engineering arena. It is free for the first 12 months and allows you to try out all of the GCP products. It will be very helpful in the pursuit of preparing for the Google Professional Data Engineer certification.

You can also enroll in the Whizlabs Google Professional Data Engineer practice tests to prepare well and pass the exam on the first attempt. Try Free Test now!

  1. Register for the Examination

When you have commenced with your preparation and are confident to take on the examination, go ahead and register for the same. You will be requested to log in to the Google Webassessor account, to proceed further with the registration process. If you haven’t created an account, then you need to sign-up and help yourself by completing the procedure.

Follow the directed steps, enter the asked information, select the mode of test you prefer, choose the location center (for on-site examination only), and make the payment. Your registration is complete! Continue with the preparation, and give your best in the examination.

Tips to Clear the Google Professional Data Engineer Certification

Here are some of the tips that will help you boost your preparation efforts of clearing the data engineer certification by Google:

  • Make sure you complete all the courses offered by the official learning path by GCP.
  • Download the cheatsheet for Google Data Engineer from GitHub.
  • Spare some preparation time for this official study guide for detailed knowledge on data engineering concepts.
  • Keep practicing the sample papers, and evolve your preparation techniques until you are satisfied with the results.

These are a few of the tips that you need to blend with your existing preparation strategy.

Salary of Google Professional Data Engineer Certified Individual

The average salary for a Google Professional Data Engineer in the USA is around $147,000 per year. It is a whooping pay-out for this profession that gives clarity on the career-oriented scope. The lowest entry-level salary of a Google Data Engineer is $141,375 per year, whereas the highest pay-out for experienced data engineers is recorded to be $175,000 per year.

Therefore, you can conclude that Google Data Engineer certification is the best you can pursue to obtain a high-paying job. With experience over time, the salary will also hike gradually.

Final Words

Google Professional Data Engineer certification is the proficient ladder for a successful career. Everyone who intends to build their career within the Cloud infrastructure can take up data engineering and other associated certification examinations to master their skills and enhance their potential. Hence, it will help individuals seek a job in high-paying companies with reputed designations.

It is very important to choose the right preparation resources for your exam preparation. To help our learners prepare well, we offer an online course and practice tests for the Google Professional Data Engineer certification exam. Enroll now and start preparing for the exam!

About Pavan Gumaste

Pavan Rao is a programmer / Developer by Profession and Cloud Computing Professional by choice with in-depth knowledge in AWS, Azure, Google Cloud Platform. He helps the organisation figure out what to build, ensure successful delivery, and incorporate user learning to improve the strategy and product further.

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