Google Cloud · Professional
Google Cloud Professional Data Engineer
Design, build, and operationalize data processing systems on Google Cloud.
Professional Data Engineer exam at a glance
| Exam code | — |
|---|---|
| Vendor | Google Cloud |
| Level | Professional |
| Domains | 5 |
| Published practice questions | 252 |
| Our mock exam | 50 questions in 120 minutes |
| Our practice pass target | 70% |
| Checked against the exam guide | July 6, 2026 |
| Official exam page | Google Cloud — Professional Data Engineer |
The mock exam length, time limit and pass target are our practice settings, not official exam scores or a guarantee of passing. Check the official Professional Data Engineer exam page for the current format, price and scoring before you book.
Professional Data Engineer exam domains
Weights show our practice allocation, built from the official exam guide; official blueprints may give ranges. Each domain links to its free sample questions (with explanations) and study guide preview once they are published.
Designing data processing systems
22%Design storage, processing, and migration architectures with security, compliance, reliability, and flexibility in mind.
- Choosing storage/processing services for batch vs streaming
- Schema design for BigQuery, Bigtable, Firestore, Spanner
- Data encryption (CMEK), DLP API, data residency and compliance
- Designing for reliability: SLAs, fault tolerance, disaster recovery
- Migration planning: Transfer Service, Datastream, BigQuery Data Transfer
- Data mesh and Dataplex concepts
- Trade-offs: cost vs performance vs latency
Free Designing data processing systems practice questions →Designing data processing systems study guide →
Ingesting and processing data
25%Build and operationalize batch and streaming pipelines.
- Pub/Sub: ordering, exactly-once, dead-letter topics, push vs pull
- Dataflow (Apache Beam): windowing, watermarks, triggers, late data
- Dataflow autoscaling, streaming engine, batch vs streaming jobs
- Dataproc for Spark/Hadoop workloads, ephemeral clusters
- Cloud Data Fusion and Composer (Airflow) orchestration
- ELT into BigQuery: load jobs, streaming inserts, Storage Write API
- Datastream change data capture
Free Ingesting and processing data practice questions →Ingesting and processing data study guide →
Storing the data
20%Select and optimize storage systems for analytical and operational workloads.
- BigQuery storage: partitioning, clustering, materialized views
- BigQuery slots, on-demand vs capacity pricing, BI Engine
- Bigtable schema/row-key design, hotspotting avoidance
- Cloud Storage classes and lifecycle for data lakes
- Spanner vs Cloud SQL selection and scaling
- Analytics Hub data sharing
- Dataplex lakes/zones and metadata management
Free Storing the data practice questions →Storing the data study guide →
Preparing and using data for analysis
15%Prepare data for analysts and support visualization, sharing, and basic ML.
- BigQuery SQL: arrays/structs, window functions, UDFs
- Authorized views, row/column-level security, policy tags
- Looker Studio and BI tool connectivity
- BigQuery ML model types and use cases
- Vertex AI integration basics, notebooks
- Dataform/dbt-style transformation workflows
Free Preparing and using data for analysis practice questions →Preparing and using data for analysis study guide →
Maintaining and automating workloads
18%Optimize, monitor, troubleshoot, and automate data workloads.
- Cloud Composer DAG scheduling and dependencies
- Workflows and Cloud Scheduler
- Monitoring pipelines: Dataflow job metrics, BigQuery INFORMATION_SCHEMA
- Cost optimization: slot reservations, query optimization, storage costs
- Error handling and retry strategies in pipelines
- Quotas and limits troubleshooting
- CI/CD for data pipelines
Free Maintaining and automating workloads practice questions →Maintaining and automating workloads study guide →
Professional Data Engineer FAQ
How is the Professional Data Engineer practice assessment configured?
Our practice format targets 50 questions in 120 minutes. Availability depends on the published question bank and is shown on this course page. Official exam question counts and formats may differ.
What does the 70% practice target mean?
Check the provider's current exam guide for official scoring. A practice percentage is not an official scaled score. DataCertPrep uses 70% as an internal practice target, not a prediction or guarantee of passing.
How should I assess my progress in Professional Data Engineer?
Use practice accuracy to find weak topics. Repeating familiar questions can inflate your score. Check coverage of the current objectives, practise hands-on tasks, and assess yourself on unseen questions.
What is the best way to study Professional Data Engineer?
Read the available guides, work through practice explanations, use flashcards and complete practical exercises. Take a timed assessment when available. Check the provider's current exam guide before booking your exam.
Should I use Professional Data Engineer exam dumps?
No. "Dumps" are questions copied or recalled from the live exam. Certification exams are covered by a candidate agreement that prohibits sharing or using them, and breaking it can lead to a revoked certification or a ban from future exams. Dumps are also often wrong, and they go out of date when the exam blueprint changes. Memorising answers does not build the skills the exam tests. Study the official Google Cloud exam guide and practise with original questions that explain each answer, such as the free sample questions linked on this page.