Google Cloud gives one associate-level certification and eight professional certifications across cloud architecture, security, DevOps, and machine learning. The GCP Data Engineer certification is one of the most desired-after among big data and analytics professionals.
Reasons for Getting Certified As a GCP Data Engineer
In the 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 change in their ability to do work itself, there are numerous other benefits too.
1: GCP Data Engineer Certification Raises Chances of Getting Hired
Certifications play a crucial role in explaining to potential employers that you are skilled. It is common in most job descriptions for data engineer roles to require an active certificate. GCP Professional certification is highly desirable, where a certificate is a plus, even if you have a wide range of skills and experiences.
2: GCP-PDE Certification Helps You Negotiate Better Salaries
The Google Cloud Data Engineer certification holds third among the top-paying certifications worldwide. Certified Google Cloud engineers require an average salary of $114,636 but often earn a lot more.
3: GCP Data Engineer Certification Improves Growth Opportunities
Certifications regularly catalyze careers, allowing them to grow within their organization to leadership positions or move to more challenging employment. 8% of those surveyed said they received promotions on creating 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 needs no requirements from candidates wishing to take the exam. It does not want you to have any other formal qualification either. It recommends 3+ years of industry experience with a year in GCP technologies, but you can take it without that.
Tips to Prepare You for the Google Cloud Data Engineer GCP-PDE Exam
To succeed in the Google Data Engineer GCP-PDE certification exam, you will need to get the concepts you will be tested on, get hands-on experience, and take practice exams.
Tip 1: Learn the Concepts You’ll Be Tested On
Google Cloud gives a clear exam guide outlining all the concepts and practices you will be tested on. The curriculum is structured following four sections: Designing data processing systems, building and operationalizing data processing systems, operationalizing machine learning models, and securing solution quality.
Spend time learning them thoroughly. Start with Google’s resources, including the learning path, webinars, and other documentation. But do not stop there. Explore other external resources for a deeper understanding.
Tip 2: Gain Hands-on Experience
Recognize that The Google Cloud Data Engineer certification is a practitioner’s exam. It wants you to have practical knowledge and experience in tech. If you then work on GCP, you might run trial workloads as part of your job. If not, you can do the free tier on GCP to set up a sandbox and practice your skills.
Tip 3: Take GCP-PDE Practice Exams
There are several resources available that can assist you in getting a view of how the exam is conducted. Google itself gives GCP Data Engineer sample questions that you can use to prepare. Spend time testing yourself on different sets of GCP-PDE questions before you schedule your exam.
What Should You Require 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 comprises multiple-choice or multiple-select questions in both English and Japanese. Major topics included are:
- Data storage, data analytics, machine learning, and data processing.
- Products such as BigQuery, Apache Hadoop, Cloud data flow, TensorFlow, stack driver, etc.
- Use cases, best practices, and case learn from different Google projects.
Where Can You Practice for the GCP Data Engineer Exam?
Begin with the Google sample exams. But do not restrict yourself to just those. Look at exams from the past few years and learn what has become. There are various other free and paid resources you can use, such as VMExam, etc. Choose ones that are right for you.
Ready to Switch Careers to Data Engineering?
Data Engineering is currently one of tech’s fastest-growing sectors. Data Engineers enjoy high job satisfaction, different creative challenges, and a chance to work with ever-evolving technologies. You will work with a one-on-one mentor to learn critical aspects of data engineering, including designing, building, and maintaining scalable data pipelines, working with the ETL framework, and retaining essential data engineering tools like MapReduce, Apache Hadoop, and Spark. You will also complete two capstone projects focused on real-world data engineering problems that you can showcase in job interviews.
