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Updated: Oct 08, 2026

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Google Professional-Data-Engineer Exam Overview:

Certification Vendor:Google Cloud
Exam Name:Google Cloud Certified Professional Data Engineer Exam
Exam Number:Professional Data Engineer
Related Certifications:Google Cloud Certified - Associate Cloud Engineer
Google Cloud Certified - Professional Machine Learning Engineer
Google Cloud Certified - Professional Data Analytics Engineer
Google Cloud Certified - Professional Cloud Architect
Exam Format:multiple choice, case study, multiple select
Real Exam Qty:Approximately 50–60 multiple choice and multiple select questions
Exam Price:$200 USD
Exam Duration:120 minutes
Passing Score:Not publicly disclosed (scaled scoring system)
Certificate Validity Period:2 years
Available Languages:Spanish, Japanese, French, Portuguese, German, English
Recommended Training:Google Cloud Data Engineering Learning Path
Google Cloud Professional Data Engineer Course (Coursera)
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

Who is the Professional Data Engineer Exam Intended for?

This exam is designed for individuals who are experts in designing, building, securing, and monitoring data processing systems with a particular emphasis on compliance and security. The candidate who wants to take the Professional Data Engineer exam should have the ability to deploy, leverage, and training pre-existing machine learning models. Moreover, every applicant should have experience of more than 3 years including 1-year experience in designing and handling solutions utilizing GCP.

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

Ensuring Solution Quality

The last section of the certification exam evaluates the ability of the learners to design for security & compliance, including identity & access management, legal compliance, data security, and privacy ensuring. Moreover, they should be able to ensure flexibility & portability, reliability & fidelity, as well as scalability & efficiency.

Google Professional-Data-Engineer Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Operationalizing machine learning models26%- Model deployment and monitoring
  • 1. Model monitoring and drift detection
    • 2. Online vs batch prediction
      - ML pipeline integration
      • 1. Vertex AI pipeline deployment
        • 2. Feature engineering and feature stores
          Topic 2: Building and operationalizing data processing systems24%- Data processing and transformation
          • 1. ETL/ELT pipeline design
            • 2. Using Dataproc, Dataflow, and BigQuery SQL
              - Data ingestion and integration
              • 1. Streaming ingestion (Pub/Sub, Dataflow)
                • 2. Batch ingestion pipelines (BigQuery, Cloud Storage)
                  Topic 3: Ensuring solution quality28%- Security and governance
                  • 1. IAM and access control in GCP
                    • 2. Data governance and compliance
                      - Reliability and performance
                      • 1. Fault tolerance and recovery strategies
                        • 2. Monitoring pipelines and workloads
                          Topic 4: 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. Latency, throughput, and consistency trade-offs
                                • 2. Event-driven vs batch architectures

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