Professional Data Engineer
A Professional Data Engineer enables data-driven decision
making by collecting, transforming, and visualizing data.
The Data Engineer designs, builds, maintains, and troubleshoots
data processing systems with a particular emphasis on the
security, reliability, fault-tolerance, scalability, fidelity,
and efficiency of such systems.
The Data Engineer also analyzes data to gain insight into
business outcomes, builds statistical models to support
decision-making, and creates machine learning models to
automate and simplify key business processes.
The Google Cloud Certified - Professional Data Engineer exam
assesses your ability to:
Build and maintain data structures and databases
Design data processing systems
Analyze data and enable machine learning
Model business processes for analysis and optimization
Design for reliability
Visualize data and advocate policy
Design for security and compliance
This exam is available in English, Japanese, Spanish, and Portuguese.
About this certification exam
This exam objectively measures an individual’s ability to demonstrate the
critical job skills for the role. To earn this certification you must pass
the Professional Data Engineer exam. The format is multiple choice and multiple
select. The exam has no prerequisites.
This exam must be taken in-person at one of our testing center locations.
Locate a test center near you.
Length: 2 hours
Registration fee: USD $200
Language: English, Japanese, Spanish, Portuguese
Path to Success
Review the exam guide
View an outline of the
topics that may appear on the exam and you are expected to know in order to
demonstrate proficiency. Some of the questions on the exam may refer you to a
case study that describes a fictitious business and solution concept. Review
the sample case studies
that may appear on your exam.
Take the training courses
Choose from on-demand or instructor led training
Data Engineering on Google Cloud Platform Specialization with Coursera:
- Google Cloud Platform Big Data and Machine Learning Fundamentals
- Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform
- Serverless Data Analysis with Google BigQuery and Cloud Dataflow
- Serverless Machine Learning with Tensorflow on Google Cloud Platform
- Building Resilient Streaming Systems on Google Cloud Platform
Practice with Qwiklabs
Get hands-on practice working with Google Cloud technologies. Learn at your
own pace with a series of labs that are available on-demand. Start with
Essentials followed by the Data Engineering quest.
Visit the documentation page with overviews and in-depth
discussions on the concepts and critical components of GCP.
Draw on your own experience
We can’t stress enough the value of your own work experience. Use the provided
resources along with your work experience to prepare for this exam.
Assess your knowledge
Familiarize yourself with the type of questions that will be on the exam.
Check your readiness to take
Schedule your exam
Register and find a location near you.