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Google Google Cloud Certified GCP-DE

GCP-DE

Exam Code: GCP-DE

Exam Name: Data Engineer

Updated: Oct 07, 2026

Q & A: 77 Questions and Answers

GCP-DE Free Demo download:

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GCP-DE PDF Price: $129.00  $59.99


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Google GCP-DE Exam Syllabus Topics:

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

Google Data Engineer Sample Questions:

Question #1
Which of the following job types are supported by Cloud Dataproc (select 3 answers)?

A. Spark
B. YARN
C. Hive
D. Pig


Question #2
You operate an IoT pipeline built around Apache Kafka that normally receives around 5000 messages per second. You want to use Google Cloud Platform to create an alert as soon as the moving average over 1 hour drops below 4000 messages per second. What should you do?

A. Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to BigQuer
B. Consume the stream of data in Cloud Dataflow using Kafka I
C. Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su
D. If that number falls below 4000, send an alert.
E. Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
F. Use Cloud Scheduler to run a script every hour that counts the number of rows created in Cloud Bigtable in the last hour
G. Set a sliding time window of 1 hour every 5 minute
H. If that number falls below 4000, send an alert.
I. Use Cloud Scheduler to run a script every five minutes that counts the number of rows created in BigQuery in the last hour
J. Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su
K. Set a fixed time window of 1 hour.Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
L. Consume the stream of data in Cloud Dataflow using Kafka I
M. Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to Cloud Bigtabl


Question #3
Which Google Cloud Platform service is an alternative to Hadoop with Hive?

A. Cloud Dataflow
B. Cloud Bigtable
C. BigQuery
D. Cloud Datastore


Question #4
You architect a system to analyze seismic dat
a. Your extract, transform, and load (ETL) process runs as a series of MapReduce jobs on an Apache Hadoop cluster. The ETL process takes days to process a data set because some steps are computationally expensive. Then you discover that a sensor calibration step has been omitted. How should you change your ETL process to carry out sensor calibration systematically in the future?

A. Introduce a new MapReduce job to apply sensor calibration to raw data, and ensure all other MapReduce jobs are chained after this.
B. Develop an algorithm through simulation to predict variance of data output from the last MapReduce job based on calibration factors, and apply the correction to all data.
C. Add sensor calibration data to the output of the ETL process, and document that all users need to apply sensor calibration themselves.
D. Modify the transformMapReduce jobs to apply sensor calibration before they do anything else.


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


Solutions:

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

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