Google Professional Data Engineer Practice Exams

The Google Professional Data Engineer (PDE) certification is Google Cloud's flagship credential for data engineers who design, build, and operationalise data processing systems on Google Cloud. It validates that you can take raw data from many sources, land it reliably in storage, transform it with batch and streaming pipelines, expose it for analytics and machine learning, and run the resulting workloads in production with security, cost control, and reliability in mind.

The exam targets working data engineers with at least three years of industry experience, including one or more years designing and managing solutions using Google Cloud. Candidates are expected to be fluent with BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud SQL, Spanner, Bigtable, Datastream, Dataplex, and the Vertex AI data and feature tooling. Questions assume you can choose the right service for a workload, write SQL against partitioned and clustered tables, design Beam or Spark pipelines, and apply IAM, CMEK, VPC Service Controls, and column-level security.

The exam contains 50 to 60 multiple-choice and multiple-select questions delivered in a single two-hour session. It is offered online with a remote proctor or at a Kryterion testing centre and costs USD 200. Google does not publish a passing score; community reports place it around 70 percent. Many questions are scenario based and test trade-offs between similar services, such as Bigtable versus BigQuery for time-series, or Dataflow versus Dataproc for batch ETL, so memorising features is not enough.

Realistic practice exams are essential because the PDE blueprint is broad and the question style rewards judgement, not recall. You need to recognise when a 'cheaper' answer fails a stated SLA, when a streaming pipeline needs a tumbling window versus a session window, when partitioning by date is wrong because the predicate uses a different column, and when a Dataproc autoscaling policy will create stragglers. Sustained scenario practice trains exactly this judgement.

Our 25 sets of 20 questions cover all five official PDE domains in proportion to the published weights. Every question includes a detailed explanation that walks through why the chosen service or technique is right and why each alternative falls short in the given scenario. The first set is completely free, no account required, and the full bank includes hundreds of unique questions across BigQuery optimisation, Dataflow window semantics, Pub/Sub delivery guarantees, Bigtable schema design, ML on structured data, governance with Dataplex and Data Catalog, and pipeline orchestration with Cloud Composer.