Google Data Engineer : GCP-DE

GCP-DE real exams

Exam Code: GCP-DE

Exam Name: Data Engineer

Updated: Aug 03, 2026

Q & A: 77 Questions and Answers

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Google GCP-DE Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Ensuring solution quality20%-25%- Data quality management
  • 1. Maintain metadata and lineage
  • 2. Implement data governance
  • 3. Validate and clean data
- Security and compliance
  • 1. Protect sensitive data
  • 2. Manage IAM and access control
  • 3. Implement encryption and compliance controls
Topic 2: Managing and optimizing solutions20%-25%- Reliability and scalability
  • 1. Implement disaster recovery strategies
  • 2. Design highly available systems
  • 3. Scale data workloads efficiently
- Managing resources and costs
  • 1. Control operational costs
  • 2. Optimize storage and compute usage
  • 3. Tune query and pipeline performance
Topic 3: Designing data processing systems22%-27%- Designing data pipelines
  • 1. Build ETL and ELT pipelines
  • 2. Design orchestration workflows
  • 3. Optimize pipeline performance and cost
- Designing for data ingestion
  • 1. Design batch and streaming ingestion solutions
  • 2. Design scalable and reliable ingestion architecture
  • 3. Select appropriate storage systems
Topic 4: Building and operationalizing data processing systems28%-33%- Operationalizing systems
  • 1. Manage logging and alerting
  • 2. Implement fault tolerance and recovery
  • 3. Monitor data pipelines and workloads
- Building data processing systems
  • 1. Implement batch processing systems
  • 2. Use BigQuery, Dataflow, Pub/Sub, Dataproc and related services
  • 3. Implement streaming data systems

Google Data Engineer Sample Questions:

1. Which of these rules apply when you add preemptible workers to a Dataproc cluster (select 2 answers)?

A) A Dataproc cluster cannot have only preemptible workers.
B) Preemptible workers cannot store data.
C) Preemptible workers cannot use persistent disk.
D) If a preemptible worker is reclaimed, then a replacement worker must be added manually.


2. You want to automate execution of a multi-step data pipeline running on Google Cloud. The pipeline includes Cloud Dataproc and Cloud Dataflow jobs that have multiple dependencies on each other. You want to use managed services where possible, and the pipeline will run every day. Which tool should you use?

A) Cloud Composer
B) Cloud Scheduler
C) cron
D) Workflow Templates on Cloud Dataproc


3. Which Cloud Dataflow / Beam feature should you use to aggregate data in an unbounded data source every hour based on the time when the data entered the pipeline?

A) An event time trigger
B) A processing time trigger
C) The with Allowed Lateness method
D) An hourly watermark


4. Which row keys are likely to cause a disproportionate number of reads and/or writes on a particular node in a Bigtable cluster (select 2 answers)?

A) A timestamp followed by a stock symbol
B) A non-sequential numeric ID
C) A sequential numeric ID
D) A stock symbol followed by a timestamp


5. You are planning to use Google's Dataflow SDK to analyze customer data such as displayed below. Your project requirement is to extract only the customer name Passing Certification Exams Made Easy visit - https://www.2PassEasy.com from the data source and then write to an output PCollection.
Tom,555 X street Tim,553 Y street Sam, 111 Z street
Which operation is best suited for the above data processing requirement?

A) Sink API
B) ParDo
C) Data extraction
D) Source API


Solutions:

Question # 1
Answer: A,B
Question # 2
Answer: D
Question # 3
Answer: B
Question # 4
Answer: A,C
Question # 5
Answer: B

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