Google Cloud

Google Cloud Professional Data Engineer

PDEPractice Exam & Study Guide

50

Exam Questions

120

Minutes

70%

Passing Score

145+

Practice Questions

The Professional Data Engineer exam validates the ability to design, build, operationalize, and secure robust, scalable, and reliable data processing systems on Google Cloud. It tests a candidate's proficiency in selecting the right storage and processing tools based on specific business requirements, performance needs, and cost constraints. This exam is intended for data engineers, data architects, and developers who have experience implementing data processing systems. Candidates should be comfortable with both batch and streaming data patterns, as well as the integration of machine learning models into data pipelines.

Cost: $200Valid: 2 yearsAvg study: 8 weeks

Take a Free PDE Diagnostic Quiz

12 questions to assess your readiness. Get a personalized study plan in 5 minutes.

Start Free Diagnostic

No credit card required

Exam Domains

Design Data Processing Systems22%

33 practice questions available

Ingest and Process Data25%

33 practice questions available

Store the Data20%

30 practice questions available

Prepare and Use Data for Analysis15%

22 practice questions available

Maintain and Automate Data Workloads18%

27 practice questions available

PDE Preparation Tips

Master the differences between BigQuery, Bigtable, Spanner, and Cloud Storage based on latency and consistency requirements.

Understand the 'Lambda' and 'Kappa' architectures and how to implement them using Dataflow and Pub/Sub.

Study the specific windowing functions in Apache Beam (Fixed, Sliding, Session) for streaming data.

Learn how to optimize BigQuery performance using partitioning, clustering, and materialized views.

Understand the role of Cloud Composer (Airflow) for workflow orchestration and DAG management.

Deep dive into Dataproc for migrating Hadoop/Spark workloads from on-premises to GCP.

Review the basics of Vertex AI and how to deploy pre-trained models or custom models for data pipelines.

Study IAM roles and permissions specifically for data services to ensure the principle of least privilege.

Practice identifying 'hotspotting' in Bigtable and how to design row keys to avoid it.

Analyze the trade-offs between different data ingestion methods: Cloud Datafusion vs. Dataflow vs. Storage Transfer Service.

Exam Day Tips for PDE

1.

Read the scenario carefully; look for keywords like 'lowest cost', 'lowest latency', or 'minimal operational overhead'.

2.

Use the process of elimination for multiple-choice questions, especially when comparing two similar GCP services.

3.

Manage your time strictly; if a complex architecture question takes too long, flag it and move on.

4.

Pay close attention to the specific requirements of the business case (e.g., 'real-time' vs 'near real-time').

5.

Ensure your system requirements are met if taking the exam via remote proctoring to avoid technical delays.

Key Google Cloud Services to Know

BigQueryCloud DataflowCloud Pub/SubCloud BigtableCloud SpannerCloud StorageCloud ComposerCloud DataprocCloud DataprepVertex AICloud DatafusionCloud SQLIAMCloud MonitoringCloud Logging

Ready to Pass PDE?

145+ practice questions, 3 full mock exams, AI-powered study plan.