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Updated: Aug 22, 2026

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Google Professional-Data-Engineer Certification Exam is designed for professionals who want to demonstrate their skills in designing and building data processing systems on the Google Cloud Platform. Google Certified Professional Data Engineer Exam certification is ideal for data engineers, data analysts, and database administrators who work with big data and want to enhance their skills. Professional-Data-Engineer exam covers a broad range of topics, including data processing, data storage, data analysis, and machine learning.

Reference: https://cloud.google.com/certification/data-engineer

Google Professional-Data-Engineer certification is a globally recognized certification that validates the skills and expertise of professionals in the field of data engineering. Google Certified Professional Data Engineer Exam certification is offered by Google and is designed to test the proficiency of individuals in designing, building, and managing data processing systems, as well as analyzing and interpreting data. Google Certified Professional Data Engineer Exam certification is aimed at individuals who are looking to enhance their career prospects in the field of data engineering.

Google Professional-Data-Engineer Exam Overview:

Certification Vendor:Google Cloud
Exam Name:Google Cloud Certified Professional Data Engineer Exam
Exam Number:Professional Data Engineer
Available Languages:English, Japanese, Spanish, Portuguese, French, German
Exam Format:multiple choice, multiple select, case study
Passing Score:Not publicly disclosed (scaled scoring system)
Related Certifications:Google Cloud Certified - Associate Cloud Engineer
Google Cloud Certified - Professional Cloud Architect
Google Cloud Certified - Professional Machine Learning Engineer
Google Cloud Certified - Professional Data Analytics Engineer
Real Exam Qty:Approximately 50–60 multiple choice and multiple select questions
Exam Duration:120 minutes
Certificate Validity Period:2 years
Exam Price:$200 USD
Recommended Training:Google Cloud Professional Data Engineer Course (Coursera)
Google Cloud Data Engineering Learning Path
Exam Registration:Google Cloud Certification Registration
Sample Questions:Google Professional-Data-Engineer Sample Questions
Exam Way:Online proctored exam or onsite test center (Kryterion Webassessor)
Pre Condition:No formal prerequisites required; recommended experience with data processing and Google Cloud Platform services
Official Syllabus URL:https://cloud.google.com/learn/certification/data-engineer

Google Professional-Data-Engineer Exam Syllabus Topics:

SectionWeightObjectives
Operationalizing machine learning models26%- Model deployment and monitoring
  • 1. Online vs batch prediction
    • 2. Model monitoring and drift detection
      - ML pipeline integration
      • 1. Vertex AI pipeline deployment
        • 2. Feature engineering and feature stores
          Ensuring solution quality28%- Reliability and performance
          • 1. Monitoring pipelines and workloads
            • 2. Fault tolerance and recovery strategies
              - Security and governance
              • 1. Data governance and compliance
                • 2. IAM and access control in GCP
                  Designing data processing systems22%- Data architecture and storage design
                  • 1. Choosing appropriate data storage solutions (relational, NoSQL, data warehouse)
                    • 2. Designing scalable and cost-effective data models
                      - Batch and streaming data processing design
                      • 1. Event-driven vs batch architectures
                        • 2. Latency, throughput, and consistency trade-offs
                          Building and operationalizing data processing systems24%- Data processing and transformation
                          • 1. Using Dataproc, Dataflow, and BigQuery SQL
                            • 2. ETL/ELT pipeline design
                              - Data ingestion and integration
                              • 1. Batch ingestion pipelines (BigQuery, Cloud Storage)
                                • 2. Streaming ingestion (Pub/Sub, Dataflow)

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