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Google Cloud · GCP-PDE · Advanced

Professional Data Engineer

Validates the ability to design, build, and operationalize data processing systems on Google Cloud that support analytics, machine learning, governance, and reliability. 45+ AI-generated practice questions with explanations. Free trial, pass guarantee.

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45 Questions
120min Time Limit
70% Pass Score
$200 USD Exam Fee

Overview

About the exam

The Professional Data Engineer certification validates the ability to design, build, and operationalize data processing systems on Google Cloud. It covers the full data engineering lifecycle including data ingestion, transformation, storage, analysis, and automation using services like BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Composer.

This certification is one of Google Cloud's most in-demand credentials, reflecting the critical role data engineers play in enabling analytics and machine learning at scale.

Exam Domains

What's on the exam

The exam features 40-50 multiple-choice and multiple-select questions over 2 hours. Note the lower question count compared to other GCP exams, giving you more time per question. Questions present complex data scenarios requiring you to choose the right architecture, storage solution, or processing approach.

Designing data processing systems 22%
Ingesting and processing the data 25%
Storing the data 20%
Preparing and using data for analysis 15%
Maintaining and automating data workloads 18%

Format

What to expect

multiple choice
80%
multiple response
20%

Watch out

Where candidates struggle

This exam requires deep understanding of Google Cloud's data ecosystem. Candidates often underestimate the breadth of services covered and the need to understand trade-offs between different storage and processing options.

  1. 01
    BigQuery Optimization — Not understanding partitioning, clustering, and materialized views for query optimization
  2. 02
    Dataflow vs Dataproc — Confusing when to use Dataflow (Apache Beam) vs Dataproc (Hadoop/Spark) for processing
  3. 03
    Streaming Architecture — Misunderstanding exactly-once processing, windowing, and watermarks in streaming pipelines
  4. 04
    Data Security — Overlooking encryption, DLP, and column-level security in BigQuery
  5. 05
    ML Readiness — Not understanding how to prepare and serve data for machine learning with BigQuery ML and Vertex AI

Details

Exam logistics

Delivered via Pearson VUE online or at testing centers. Available in English and Japanese. The certification is valid for 2 years with a renewal exam option (20 questions, 1 hour, $100).

Delivery Online-proctored (Pearson VUE) or onsite-proctored at testing centers
Retake policy 14-day wait after a failed attempt. No limit on retakes.
Validity 2 years
Career outcomes Data engineer, analytics engineer, data platform engineer, and ML infrastructure engineer roles on Google Cloud.
Renewal Certification valid for 2 years. Renewal exam available (20 questions, 1 hour, $100) within the renewal eligibility period.
Study time ~100 hours
Official guide View on vendor site

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