Google Data Engineer : GCP-DE

Pass GCP-DE Exam Cram

Exam Code: GCP-DE

Exam Name: Data Engineer

Updated: Sep 16, 2026

Q & A: 77 Questions and Answers

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Google GCP-DE Exam Syllabus Topics:
SectionWeightObjectives
Topic 1: Preparing data for analysis and machine learning13%- Preparing data for ML
  • 1. Feature engineering and data preparation
  • 2. Supporting model training and serving
- Enabling data analysis
  • 1. Implementing data sharing and governance
  • 2. Optimizing query performance
  • 3. Preparing datasets for querying and reporting
Topic 2: Maintaining and automating data workloads18%- Operationalizing workloads
  • 1. Ensuring reliability and recoverability
  • 2. Orchestrating and scheduling jobs
  • 3. Monitoring and troubleshooting pipelines
- Automation and optimization
  • 1. Optimizing resource usage and costs
  • 2. Automating deployment and management
Topic 3: Designing data processing systems24%- Planning data solutions
  • 1. Designing for reliability, scalability, and efficiency
  • 2. Selecting appropriate storage solutions
  • 3. Planning for data security and compliance
- Designing data pipelines
  • 1. Designing for data transformation and enrichment
  • 2. Defining architecture for batch and streaming processing
  • 3. Planning for data migration and integration
Topic 4: Ingesting and processing data25%- Transforming data
  • 1. Applying data processing logic
  • 2. Managing schema evolution
  • 3. Optimizing transformations for performance
- Building data pipelines
  • 1. Handling data quality and consistency
  • 2. Developing batch and streaming workflows
  • 3. Implementing ingestion mechanisms
Topic 5: Storing and managing data20%- Optimizing storage performance and cost
  • 1. Configuring storage for access patterns
  • 2. Implementing cost optimization strategies
- Implementing storage solutions
  • 1. Designing data warehouses and data lakes
  • 2. Using data storage services appropriately
  • 3. Managing data lifecycle and retention
Google Data Engineer Sample Questions:
Question #1

You are responsible for writing your company's ETL pipelines to run on an Apache Hadoop cluster. The pipeline will require some checkpointing and splitting pipelines. Which method should you use to write the pipelines?

  • A. PigLatin using Pig
  • B. Python using MapReduce
  • C. Java using MapReduce
  • D. HiveQL using Hive
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Question #2

You have historical data covering the last three years in BigQuery and a data pipeline that delivers new data to BigQuery daily. You have noticed that when the Data Science team runs a query filtered on a date column and limited to 30-90 days of data, the query scans the entire table. You also noticed that your bill is increasing more quickly than you expected. You want to resolve the issue as cost-effectively as possible while maintaining the ability to conduct SQL queries. What should you do?

  • A. Recommend that the Data Science team export the table to a CSV file on Cloud Storage and use Cloud Datalab to explore the data by reading the files directly.
  • B. Recommend that the Data Science team use wildcards on the table name suffixes to select the data they need.
  • C. Modify your pipeline to maintain the last 30-90 days of data in one table and the longer history in a different table to minimize full table scans over the entire history.
  • D. Write an Apache Beam pipeline that creates a BigQuery table per data
  • E. Re-create the tables using DD
  • F. Partition the tables by a column containing a TIMESTAMP or DATE Type.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Question #3

Which of the following is NOT one of the three main types of triggers that Dataflow supports?

  • A. Trigger based on element size in bytes
  • B. Trigger based on time
  • C. Trigger based on element count
  • D. Trigger that is a combination of other triggers
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Question #4

By default, which of the following windowing behavior does Dataflow apply to unbounded data sets?

  • A. Windows at every 100 MB of data
  • B. Windows at every 10 minutes
  • C. Single, Global Window
  • D. Windows at every 1 minute
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #5

You need to deploy additional dependencies to all of a Cloud Dataproc cluster at startup using an existing initialization action. Company security policies require that Cloud Dataproc nodes do not have access to the Internet so public initialization actions cannot fetch resources. What should you do?

  • A. Deploy the Cloud SQL Proxy on the Cloud Dataproc master
  • B. Use an SSH tunnel to give the Cloud Dataproc cluster access to the Internet
  • C. Use Resource Manager to add the service account used by the Cloud Dataproc cluster to the Network User role
  • D. Copy all dependencies to a Cloud Storage bucket within your VPC security perimeter
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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