Google Cloud Data Engineer Certification Practice Tests 2026

Prepare for the GCP Data Engineer exam with 2026 practice tests, real-style questions, detailed explanations, and domain

**Reviewed Jan 2026 | Per Latest Exam Guideline & Patterns

**Reviewed OCT/2025

**Updated May/2025

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Preparing for the Google Cloud Professional Data Engineer Certification?
This course provides the most updated, 2026-ready practice tests aligned with both:

• Google’s Standard Exam Guide
• Google’s Renewal Exam Guide

The practice tests mirror real exam question patterns and cover every domain defined by Google Cloud—including pipeline design, data governance, security, analytics, ML readiness, storage planning, and workload optimization.

You will learn to design, build, maintain, and optimize complete data solutions using BigQuery, Dataflow, Dataproc, Cloud Storage, Dataplex, AlloyDB, Bigtable, Pub/Sub, Cloud Composer, and Vertex AI.

Every question includes a clear explanation, teaching not only the correct answer—but also why the other options are incorrect.

This course gives you the skills, exam readiness, and confidence to pass on the first attempt.

What You’ll Learn (Mapped to Exam Guide Topics)

1. Designing Data Processing Systems

(From Standard Exam Guide Section 1 & Renewal Section 1)

• IAM, encryption, governance, privacy & compliance
• Designing ACID-compliant architectures
• Data cleansing, quality, lineage, validation
• Multi-environment design (dev, test, prod)
• Designing migrations with Datastream, DMS, Transfer Appliance

2. Ingesting & Processing Data (Batch + Streaming)

(Exam Guide Section 2)

• Dataflow, Apache Beam, Dataproc, Cloud Data Fusion
• Pub/Sub ingestion, streaming windows, late data handling
• Data transformation logic, AI data enrichment
• CI/CD for pipelines, automation, orchestration (Composer, Workflows)

3. Storing Data (Warehouse + Data Lake + Operational DBs)

(Exam Guide Section 3; Renewal Section 3)

• BigQuery optimization: storage, cost, normalization, partitions
• BigLake, Dataplex, federated governance
• AlloyDB, Bigtable, Spanner, Cloud SQL, Firestore
• Data lake management, cost control, metadata catalogs

4. Preparing & Using Data for Analysis, AI, and ML

(Exam Guide Section 4; Renewal Section 4)

• BI Engine, materialized views, query optimization
• Data masking, IAM, Cloud DLP
• Preparing features for ML (Vertex AI, BigQuery ML)
• Preparing unstructured data for embeddings & RAG
• Sharing datasets with Analytics Hub

5. Maintaining, Monitoring & Optimizing Data Workloads

(Exam Guide Section 5; Renewal Section 5)

• BigQuery Editions, reservations, autoscaling
• Observability with Cloud Monitoring & Logging
• Scheduling workloads, capacity planning
• Troubleshooting quotas, errors, billing, job failures
• Designing fault-tolerant data pipelines

Requirements

• Basic understanding of databases or cloud concepts
• No prior Google Cloud experience required
• The course focuses exclusively on exam-style practice tests

Who This Course is For

• Data Engineers preparing for the Google Cloud certification
• Cloud Engineers & Architects building analytics pipelines
• ML Engineers and Data Scientists working with BigQuery/Vertex AI
• Developers transitioning into data engineering roles
• Anyone wanting a top-tier Google Cloud certification

Course Includes

• Multiple full-length 2026 practice exams
• Scenario questions aligned to real exam patterns
• Detailed explanations for every question
• Domain-level readiness checks
• Lifetime access with regular updates
• Coverage of both standard and renewal exam topics

Exam Informations

• Standard exam information

  Length: 2 hours

  Exam Content: Standard exam guide

  Registration fee: $200 (plus tax where applicable)

  Languages: English, Japanese

  Exam format: 40 - 50 multiple choice and multiple select questions

  Exam Delivery Method: Online-proctored or onsite-proctored

  Validity period: 2 years

  Prerequisites: None

  Recommended experience: 3+ years of industry experience including 1+ years designing and managing data solutions using Google Cloud.

  
  

• Renewal exam information

  Length: 1 hour

  Exam Content: Renewal exam guide

  Registration fee: $100 (plus tax where applicable)

  Language: English

  Exam format: 20 multiple choice and multiple select questions

  Exam Delivery Method: Online-proctored or onsite-proctored

  Validity period: 2 years

  Eligibility: Candidates must have an active certification and be within the renewal eligibility period.

  
  

• Delivery Methods:

  • Online-proctored exam (taken remotely)

  • Onsite proctored exam (taken at a testing center)

  
  

• Validity: The certification is valid for two years.

  
  

• Exam Content Outline(v4.2) - Standard Exam

• If this is your first time getting certified, or your certification has expired, you must take the standard exam.

  If you are renewing your certification, you can choose to take the shorter renewal exam or the standard exam starting 60 days before your expiration date. Once you have chosen either the standard or renewal exam path, you will stay in that path until you pass or your certification expires.

• The Professional Data Engineer standard exam tests your ability in the following key areas:

  • • Section 1: Designing data processing systems (~22% of the exam)

      • 1.1 Designing for security and compliance.

      • 1.2 Designing for reliability and fidelity.

      • 1.3 Designing for flexibility and portability.

      • 1.4 Designing data migrations.

    • Section 2: Ingesting and processing the data (~25% of the exam)

      • 2.1 Planning the data pipelines.

      • 2.2 Building the pipelines.

      • 2.3 Deploying and operationalizing the pipelines.

    • Section 3: Storing the data (~20% of the exam)

      • 3.1 Selecting storage systems.

      • 3.2 Planning for using a data warehouse.

      • 3.3 Using a data lake.

      • 3.4 Designing for a data platform.

    • Section 4: Preparing and using data for analysis (~15% of the exam)

      • 4.1 Preparing data for visualization.

      • 4.2 Preparing data for AI and ML.

      • 4.3 Sharing data.

    • Section 5: Maintaining and automating data workloads (~18% of the exam)

      • 5.1 Optimizing resources.

      • 5.2 Designing automation and repeatability.

      • 5.3 Organizing workloads based on business requirements.

      • 5.4 Monitoring and troubleshooting processes.

      • 5.5 Maintaining awareness of failures and mitigating impact

  
  

  
  

  Exam Content Outline - Renewal Exam

• If this is your first time getting certified, or your certification has expired, you must take the standard exam.

  If you are renewing your certification, you can choose to take the shorter renewal exam or the standard exam starting 60 days before your expiration date. Once you have chosen either the standard or renewal exam path, you will stay in that path until you pass or your certification expires.

• The Professional Data Engineer Renewal exam tests your ability in the following key areas:

  
  

  • Section 1: Designing data processing systems (~25% of the exam)

    • 1.1 Designing for security and compliance.

    • 1.2 Designing for reliability and fidelity

    • 1.3 Designing for flexibility and portability.

  • Section 2: Ingesting and processing the data (~10% of the exam)

    • 2.1 Planning the data pipelines

    • 2.2 Building the pipelines

    • 2.3 Deploying and operationalizing the pipelines

  • Section 3: Storing the data (~25% of the exam)

    • 3.1 Selecting storage systems

    • 3.3 Using a data lake.

    • 3.4 Designing for a data platform

  • Section 4: Preparing and using data for analysis (~25% of the exam)

    • 4.1 Preparing data for visualization.

    • 4.2 Preparing data for AI and ML.

    • 4.3 Sharing data.

  • Section 5: Maintaining and automating data workloads (~15% of the exam)

    • 5.2 Designing automation and repeatability

    • 5.3 Organizing workloads based on business requirements

    • 5.4 Monitoring and troubleshooting processes.

• Prerequisites

  • There are no strict prerequisites, but Google recommends having at least 3+ years of industry experience with 1+ years using Google Cloud products.

Certification Renewal / Recertification: Candidates must recertify in order to maintain their certification status. Unless explicitly stated in the detailed exam descriptions, all Google Cloud certifications are valid for two years from the date of certification. Recertification is accomplished by retaking the exam during the recertification eligibility time period and achieving a passing score. You may attempt recertification starting 60 days prior to your certification expiration date.