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Professional · Professional Data EngineerPrep available

Google Cloud Certified Professional Data Engineer (Professional Data Engineer) practice exam and study path

A free, timed 50-question Professional Data Engineer practice exam in 120 minutes, scored by domain, with every option explained after you submit. Also 126 practice questions you can check one at a time, a page for every task in the exam guide, and a study path. No sign-up.

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Professional Data Engineer exam pack:

$11.99for 12 months

The Google Cloud data exam: designing secure and reliable data processing systems, building batch and streaming pipelines, choosing and modelling storage, preparing data for analysis and AI, and running data workloads at the right cost.

The exam

Exam code
Professional Data Engineer
Questions
Not yet published
Time
120 minutes
Passing score
Not published
Exam fee
$200 (USD)
Question types
multiple choice, multiple response

40-50 multiple-choice and multiple-select questions in 2 hours, $200 plus tax, online-proctored or at a test center, in English and Japanese. No prerequisites; 3+ years of industry experience including 1+ years designing and managing solutions on Google Cloud recommended; valid for 2 years. Holders can renew with the standard exam, a renewal exam (1 hour, 20 questions, $100) or designated courses and skill badges in Google Skills. The certification page says the exam will soon be updated to reflect recent branding changes; the exam guide lists the product names used on the exam. Passing score: Not published. Our forms hold 50 questions, the top of the published range, split by the guide's approximate section weights.

From Google Cloud's certification page and exam guide, checked Oct 24, 2026.

Domains and weights

  • Domain 1: Designing data processing systems

    22%

  • Domain 2: Ingesting and processing the data

    25%

  • Domain 3: Storing the data

    20%

  • Domain 4: Preparing and using data for analysis

    15%

  • Domain 5: Maintaining and automating data workloads

    18%

On our roadmap this comes after Associate Cloud Engineer. See every certification.

Practice

126 original practice questions, every option explained with the Google Cloud documentation page that proves it. Free, no sign-up; progress stays on this device.

Your results on this device →

More practice exams

The lessons, the sample questions on every task page and the first full practice exam are free and stay free. A pack adds the further timed Professional Data Engineer practice exams.

Professional Data Engineer exam pack

$11.99for 12 months

  • Every paid Professional Data Engineer practice exam, timed, with every option explained
  • The next version of this exam included when it changes within your 12 months
  • 12 months of access. One payment, nothing renews by itself.
  • 14-day refund, no conditions
  • 14-day refund, no conditions: ask within 14 days of buying and you get the whole payment back.
  • No pass guarantee. These are practice exams written by us from the exam guide and the Google Cloud documentation; a score here does not predict your result on the real exam.

Study path

One module per exam domain. Lessons that already exist on BytePatterns are linked; the rest are being written.

  1. Module 1: Designing data processing systems

    1. 1IAM for data: BigQuery roles, service accounts and organization policiesTask 1.1

      Partly covered by: Shared Responsibility & IAM, Organizations, SCPs & Control Tower

    2. 2Encryption and key management: CMEK, Cloud EKM and column-level encryptionTask 1.1

      Partly covered by: KMS, Envelope Encryption & Private CA

    3. 3PII: policy tags, row-level security, Sensitive Data Protection and data residencyTask 1.1

      Partly covered by: Finding and Masking PII

    4. 4Projects, datasets and environments for governance; VPC Service ControlsTask 1.1

      Lesson coming

    5. 5Cleaning and validating data with Dataform, Dataflow and Cloud Data FusionTask 1.2

      Partly covered by: Data Readiness for AI

    6. 6Fault tolerance, disaster recovery, and ACID versus availabilityTask 1.2

      Partly covered by: Consistency and CAP, Transactions & ACID, Disaster Recovery: RPO & RTO

    7. 7Generating SQL with Gemini in BigQueryTask 1.2

      Lesson coming

    8. 8Portability: open table formats, BigQuery Omni and Apache BeamTask 1.3

      Lesson coming

    9. 9Staging, cataloging, profiling and discovering data in Knowledge CatalogTask 1.3

      Lesson coming

    10. 10Migration planning: assessment, transfer options and validationTask 1.4

      Partly covered by: Moving Data Into AWS, Migration: The 7 Rs, TCO & Waves

    11. 11Database Migration Service, Datastream and the BigQuery Data Transfer ServiceTask 1.4

      Partly covered by: Database Replication

  2. Module 2: Ingesting and processing the data

    1. 12Sources, sinks and the pipeline shape: batch, streaming, ETL and ELTTask 2.1

      Lesson coming

    2. 13Pipeline networking and encryption: Private Google Access, Shared VPC, CMEKTask 2.1

      Partly covered by: VPC: Subnets, NAT & Firewalls, Hybrid Networking & DNS

    3. 14Streaming with Pub/Sub and Dataflow: windows, triggers, watermarks and late dataTask 2.2

      Partly covered by: Design Ad Click Aggregation

    4. 15Delivery semantics: exactly-once, at-least-once and deduplicationTask 2.2

      Partly covered by: Message Queues, Design Ad Click Aggregation

    5. 16Batch processing with Dataflow, Managed Service for Apache Spark and BigQuery SQLTask 2.2

      Partly covered by: INNER and OUTER JOINs, Window Functions

    6. 17Schema evolution, change data capture and acquiring new sourcesTask 2.2

      Lesson coming

    7. 18AI enrichment in pipelinesTask 2.2

      Lesson coming

    8. 19Orchestration with Managed Service for Apache Airflow and WorkflowsTask 2.3

      Partly covered by: Design a Job Scheduler

    9. 20CI/CD for Dataflow templates, DAGs and DataformTask 2.3

      Lesson coming

  3. Module 3: Storing the data

    1. 21Choosing a store: BigQuery, Bigtable, Spanner, Cloud SQL, AlloyDB, Firestore, MemorystoreTask 3.1

      Partly covered by: SQL vs NoSQL, RDS vs DynamoDB, Caching

    2. 22Cloud Storage classes, Autoclass and lifecycle rulesTask 3.1

      Partly covered by: S3: Consistency, Classes, Lifecycle

    3. 23Bigtable row keys and storage cost planningTask 3.1

      Partly covered by: Database Sharding

    4. 24Modelling the warehouse: normalization, nested fields, star schemas and historyTask 3.2

      Lesson coming

    5. 25Partitioning and clustering BigQuery tablesTask 3.2

      Lesson coming

    6. 26The lake on Cloud Storage: BigLake tables, Iceberg and the Lakehouse runtime catalogTask 3.3

      Lesson coming

    7. 27Lake access, cost controls and monitoringTask 3.3

      Partly covered by: S3: Consistency, Classes, Lifecycle

    8. 28A data platform on Knowledge Catalog: data mesh, data products and federated governanceTask 3.4

      Lesson coming

  4. Module 4: Preparing and using data for analysis

    1. 29Serving dashboards: BI Engine, materialized views, Data Studio and LookerTask 4.1

      Partly covered by: Caching

    2. 30Troubleshooting slow BigQuery queriesTask 4.1

      Partly covered by: Reading a Query Plan, Query Execution Order

    3. 31Masking and de-identifying what analysts seeTask 4.1

      Partly covered by: Finding and Masking PII

    4. 32Features, training and serving with BigQuery MLTask 4.2

      Partly covered by: What Is Machine Learning, Training vs Inference

    5. 33Embeddings, vector search and RAG over unstructured dataTask 4.2

      Partly covered by: Embeddings, Vector Databases, Retrieval-Augmented Generation, Chunking and Reranking

    6. 34Sharing data: BigQuery sharing, clean rooms, authorized views and published reportsTask 4.3

      Lesson coming

  5. Module 5: Maintaining and automating data workloads

    1. 35Cost and capacity: autoscaling, Spot workers, FlexRS and ephemeral clustersTask 5.1

      Partly covered by: AWS Cost Levers, Vertical vs Horizontal Scaling

    2. 36Repeatable DAGs: idempotent tasks, backfills, retries and dependenciesTask 5.2

      Partly covered by: Design a Job Scheduler

    3. 37BigQuery editions, reservations and interactive or batch jobsTask 5.3

      Lesson coming

    4. 38Monitoring and troubleshooting data workloadsTask 5.4

      Partly covered by: Observability Basics, CloudWatch, Alarms & X-Ray

    5. 39Failures and recovery: replication, failover, time travel and replayTask 5.5

      Partly covered by: Database Replication, Disaster Recovery: RPO & RTO

Every task in the exam guide

The exam guide splits each domain into task statements. Each one has a page with a short summary, the lessons that teach it and open sample questions.

Domain 1: Designing data processing systems

Domain 2: Ingesting and processing the data

Domain 3: Storing the data

Domain 4: Preparing and using data for analysis

Domain 5: Maintaining and automating data workloads

How these questions are made

  • Written by us from the exam guide's task statements and the Google Cloud documentation — never from real exam content.
  • Every option carries its own explanation and a link to the Google Cloud page that proves it.
  • A question enters a timed exam only after an independent check; until then it is a practice question.
  • Results are a plain percentage, per domain too — not an imitation of Google Cloud's scaled score.

Questions about the Professional Data Engineer practice exam

Is the Professional Data Engineer practice exam free?
Yes. The full practice exam (50 questions, 120 minutes) is free with no sign-up, and so are the 126 practice questions, the task pages and the study path. Your attempts are saved in this browser, on this device.
How many questions does it have, and is it timed?
50 questions in 120 minutes: the real Professional Data Engineer pace, scaled to this form. When the time runs out, the exam is submitted as it stands.
Are the answers explained?
After you submit, not during: like the real exam, the timed exam gives no feedback until the end. Then you get your score overall and per exam domain, and every question with each option explained and a link to the Google Cloud documentation page behind it. In practice mode an answer is explained as soon as you check it.
What does the Professional Data Engineer exam pack add?
3 more timed practice exams (Practice exam 1: 50 questions, 120 minutes; Practice exam 2: 50 questions, 120 minutes; Practice exam 3: 50 questions, 120 minutes), each scored and explained the same way, and the next version of this exam if it changes within your 12 months. 12 months of access. One payment, nothing renews by itself. Everything above stays free. See the pack.
Can I get a refund?
Yes, with no conditions: ask within 14 days of buying and you get the whole payment back. The details are in the terms.
Is this an official Google Cloud practice exam?
No. BytePatterns is not affiliated with, endorsed or sponsored by Google Cloud. Every question is written by us from the public exam guide and the Google Cloud documentation, never from real exam content, and a score here does not predict your result on the real exam. Google Cloud lists its own preparation resources on its certification page.