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Updated: Oct 06, 2026

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Google GCP-DE Exam Overview:

Certification Vendor:Google Cloud
Exam Name:Professional Data Engineer
Exam Number:GCP-DE
Related Certifications:Google Cloud Certified Professional Data Engineer
Exam Format:Multiple choice, Multiple select
Real Exam Qty:50-60
Exam Duration:120 minutes
Exam Price:$200 USD
Certificate Validity Period:2 years
Available Languages:Japanese, English
Passing Score:Not publicly disclosed
Sample Questions:Google GCP-DE Sample Questions
Exam Way:Online proctored or onsite testing center
Pre Condition:No formal prerequisites. Google recommends 3+ years of industry experience including 1+ years designing and managing solutions using Google Cloud.
Official Syllabus URL:https://cloud.google.com/learn/certification/data-engineer

Google GCP-DE Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Designing data processing systems22%-27%- Designing for data ingestion
  • 1. Design batch and streaming ingestion solutions
  • 2. Select appropriate storage systems
  • 3. Design scalable and reliable ingestion architecture
- Designing data pipelines
  • 1. Build ETL and ELT pipelines
  • 2. Design orchestration workflows
  • 3. Optimize pipeline performance and cost
Topic 2: Managing and optimizing solutions20%-25%- Managing resources and costs
  • 1. Tune query and pipeline performance
  • 2. Control operational costs
  • 3. Optimize storage and compute usage
- Reliability and scalability
  • 1. Scale data workloads efficiently
  • 2. Design highly available systems
  • 3. Implement disaster recovery strategies
Topic 3: 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. Implement encryption and compliance controls
  • 2. Protect sensitive data
  • 3. Manage IAM and access control
Topic 4: Building and operationalizing data processing systems28%-33%- Operationalizing systems
  • 1. Monitor data pipelines and workloads
  • 2. Manage logging and alerting
  • 3. Implement fault tolerance and recovery
- 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:

Question #1

Your company produces 20,000 files every hour. Each data file is formatted as a comma separated values (CSV) file that is less than 4 KB. All files must be ingested on Google Cloud Platform before they can be processed. Your company site has a 200 ms latency to Google Cloud, and your Internet connection bandwidth is limited as 50 Mbps. You currently deploy a secure FTP (SFTP) server on a virtual machine in Google Compute Engine as the data ingestion point. A local SFTP client runs on a dedicated machine to transmit the CSV files as is. The goal is to make reports with data from the previous day available to the executives by 10:00 a.m. each day. This design is barely able to keep up with the current volume, even though the bandwidth utilization is rather low.
You are told that due to seasonality, your company expects the number of files to double for the next three months. Which two actions should you take? (choose two.)

  • A. Contact your internet service provider (ISP) to increase your maximum bandwidth to at least 100 Mbps.
  • B. Redesign the data ingestion process to use gsutil tool to send the CSV files to a storage bucket in parallel.
  • C. Create an S3-compatible storage endpoint in your network, and use Google Cloud Storage Transfer Service to transfer on-premices data to the designated storage bucket.
  • D. Introduce data compression for each file to increase the rate file of file transfer.
  • E. Transmit the TAR files instead, and disassemble the CSV files in the cloud upon receiving them.
  • F. Assemble 1,000 files into a tape archive (TAR) fil
Reveal Solution  Discussion  0

Correct Answer: B,E  🗳️

Question #2

Suppose you have a table that includes a nested column called "city" inside a column called "person", but when you try to submit the following query in BigQuery, it gives you an error.
SELECT person FROM `project1.example.table1` WHERE city = "London"
How would you correct the error?

  • A. Add ", UNNEST(person)" before the WHERE clause.
  • B. Change "person" to "city.person".
  • C. Change "person" to "person.city".
  • D. Add ", UNNEST(city)" before the WHERE clause.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Question #3

All Google Cloud Bigtable client requests go through a front-end server they are sent to a Cloud Bigtable node.

  • A. after
  • B. only if
  • C. before
  • D. once
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #4

You are implementing several batch jobs that must be executed on a schedule. These jobs have many interdependent steps that must be executed in a specific order. Portions of the jobs involve executing shell scripts, running Hadoop jobs, and running queries in BigQuery. The jobs are expected to run for many minutes up to several hours. If the steps fail, they must be retried a fixed number of times. Which service should you use to manage the execution of these jobs?

  • A. Cloud Functions
  • B. Cloud Scheduler
  • C. Cloud Composer
  • D. Cloud Dataflow
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Question #5

You are planning to migrate your current on-premises Apache Hadoop deployment to the cloud. You need to ensure that the deployment is as fault-tolerant and cost-effective as possible for long-running batch jobs. You want to use a managed service. What should you do?

  • A. Use an SSD persistent disk and 50% preemptible worker
  • B. Use a standard persistent disk and 50% preemptible worker
  • C. Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://
  • D. Change references in scripts from hdfs:// to gs://
  • E. Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://
  • F. Install Hadoop and Spark on a 10-node Compute Engine instance group with standard instance
  • G. Deploy a Cloud Dataproc cluste
  • H. Install the Cloud Storage connector, and store the data in Cloud Storag
  • I. Install Hadoop and Spark on a 10-node Compute Engine instance group with preemptible instances.Store data in HDF
  • J. Change references in scripts from hdfs:// to gs://
  • K. Deploy a Cloud Dataproc cluste
Reveal Solution  Discussion  0

Correct Answer: G  🗳️

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