Google Data Engineer : GCP-DE valid dumps

GCP-DE real exams

Exam Code: GCP-DE

Exam Name: Data Engineer

Updated: Sep 08, 2026

Q & A: 77 Questions and Answers

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Here is a piece of math most GCP-DE candidates learn too late: the study material costs a fraction of one retake. The Google Data Engineer practice questions at Actual4Exams, 77 of them, exist so that your first exam fee is your only exam fee.

Google GCP-DE Exam Overview:

Certification Vendor:Google Cloud
Exam Name:Professional Data Engineer
Exam Number:GCP-DE
Available Languages:Japanese, English
Real Exam Qty:50-60
Exam Format:Multiple select, Multiple choice
Related Certifications:Google Cloud Certified Professional Data Engineer
Passing Score:Not publicly disclosed
Certificate Validity Period:2 years
Exam Duration:120 minutes
Exam Price:$200 USD
Sample Questions:Free Download GCP-DE valid dump
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: 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. Manage IAM and access control
  • 3. Protect sensitive data
Topic 2: Managing and optimizing solutions20%-25%- Reliability and scalability
  • 1. Implement disaster recovery strategies
  • 2. Scale data workloads efficiently
  • 3. Design highly available systems
- Managing resources and costs
  • 1. Optimize storage and compute usage
  • 2. Tune query and pipeline performance
  • 3. Control operational costs
Topic 3: Designing data processing systems22%-27%- Designing for data ingestion
  • 1. Design batch and streaming ingestion solutions
  • 2. Design scalable and reliable ingestion architecture
  • 3. Select appropriate storage systems
- Designing data pipelines
  • 1. Build ETL and ELT pipelines
  • 2. Optimize pipeline performance and cost
  • 3. Design orchestration workflows
Topic 4: Building and operationalizing data processing systems28%-33%- Building data processing systems
  • 1. Use BigQuery, Dataflow, Pub/Sub, Dataproc and related services
  • 2. Implement streaming data systems
  • 3. Implement batch processing systems
- Operationalizing systems
  • 1. Monitor data pipelines and workloads
  • 2. Manage logging and alerting
  • 3. Implement fault tolerance and recovery

The Google GCP-DE Exam, Question by Question

Google Data Engineer is an official exam run by Google Cloud under exam code GCP-DE. Passing it awards the Google Cloud Certified certification, which sits at the Professional tier. It also counts toward related credentials such as Google Cloud Certified Professional Data Engineer. Certified professionals remain in shorter supply than the market wants, which is precisely why this exam keeps showing up in conversations about better roles and better pay.

The Google Data Engineer exam gives you 120 minutes to work through 50-60 questions. That is a tight ratio, and it punishes candidates who get emotionally attached to any single item. The fix is mechanical: answer what you know, flag what you do not, and keep moving. A few full-length timed runs in the Actual4Exams test engine, with its randomized question order, will calibrate your pace far better than untimed reading ever could.

The official fee for Google Data Engineer is $200 USD, and Not publicly disclosed is what passing takes. The uncomfortable part: retakes cost the full $200 USD again, which makes preparation the cheapest line item in this whole project. Before booking, put yourself through repeated scored sessions with the Actual4Exams practice tests and compare results over time; a stable margin above the passing line, not a single lucky run, is when you are ready.

No formal prerequisites. Google recommends 3+ years of industry experience including 1+ years designing and managing solutions using Google Cloud.

Vendor rules do get revised, so treat this as your starting point and confirm the current eligibility details before booking via the official exam page.

It is. Actual4Exams publishes a free PDF demo of the Google Data Engineer material, so the product can prove itself before you pay. Your purchase then comes with 365 days of free updates, and once that period ends, extending the update service costs 50% of the regular price. The test engine software itself is verified malware-free and safe to install.

Actual4Exams stands behind the product with a 100% money-back guarantee under defined conditions. If you take the Google Data Engineer exam within 60 days of purchase and fail, you qualify for a full refund, provided the exam corresponds to your product. Sitting the exam within 3 days of purchase does not qualify, and neither do unused downloads, free materials, or expired orders; the candidate name must match the payer name. Submit a scanned enrollment slip and the official Score Report PDF within 2 days of the exam, and claims are resolved within 7 days. You may also choose an exchange instead of a refund: two other exam products of equal value, free, with the update service on your original purchase retained.

Delivery takes about a minute. Files unlock for instant download at payment and are emailed to you automatically; if 2 hours pass with nothing received, check spam and contact customer service. There is no installation limit, so the test engine can live on every device you own, phone included.

Google Data Engineer breaks down into 4 official domains, led by Ensuring solution quality (20%-25%), Managing and optimizing solutions (20%-25%), and Building and operationalizing data processing systems (28%-33%). You will find the full topic-by-topic outline above on this page; use the weightings to budget your study hours where they pay back the most.

Google Data Engineer Sample Questions:

Question 1

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


Question 2

You are selecting services to write and transform JSON messages from Cloud Pub/Sub to BigQuery for a data pipeline on Google Cloud. You want to minimize service costs. You also want to monitor and accommodate input data volume that will vary in size with minimal manual intervention. What should you do?

A. Monitor CPU utilization for the cluste
B. Use Cloud Dataproc to run your transformation
C. Configure the job to use non-default Compute Engine machine types when needed.
D. Use the diagnose command to generate an operational output archiv
E. Monitor the total execution time for a sampling of job
F. Resize the number of worker nodes in your cluster via the command line.
G. Locate the bottleneck and adjust cluster resources.
H. Use the default autoscaling setting for worker instances.
I. Use Cloud Dataflow to run your transformation
J. Use Cloud Dataproc to run your transformation
K. Use Cloud Dataflow to run your transformation
L. Monitor the job system lag with Stackdrive


Question 3

You have a data stored in BigQuery. The data in the BigQuery dataset must be highly available. You need to define a storage, backup, and recovery strategy of this data that minimizes cost. How should you configure the BigQuery table?

A. In the event of an emergency, use a point-in-time snapshot to recover the data.
B. Set the BigQuery dataset to be multi-regional
C. Create a scheduled query to make copies of the data to tables suffixed with the time of the backup
D. In the event of an emergency, use the backup copy of the table.
E. In the event of an emergency, use a point-in-time snapshot to recover the data.
F. Set the BigQuery dataset to be multi-regional
G. In the event of an emergency, use the backup copy of the table.
H. Set the BigQuery dataset to be regiona
I. Set the BigQuery dataset to be regiona
J. Create a scheduled query to make copies of the data to tables suffixed with the time of the backu


Question 4

Each analytics team in your organization is running BigQuery jobs in their own projects. You want to enable each team to monitor slot usage within their projects. What should you do?

A. Create a Stackdriver Monitoring dashboard based on the BigQuery metric slots/allocated_for_project
B. Create a Stackdriver Monitoring dashboard based on the BigQuery metric query/scanned_bytes
C. Create an aggregated log export at the organization level, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric
D. Create a log export for each project, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric


Question 5

You have enabled the free integration between Firebase Analytics and Google BigQuery. Firebase now automatically creates a new table daily in BigQuery in the format app_events_YYYYMMDD. You want to query all of the tables for the past 30 days in legacy SQL. What should you do?

A. Use the TABLE_DATE_RANGE function
B. Use SELECT IF.(date >= YYYY-MM-DD AND date <= YYYY-MM-DD
C. Use WHERE date BETWEEN YYYY-MM-DD AND YYYY-MM-DD
D. Use the WHERE_PARTITIONTIME pseudo column


Solutions:

Question 1
Answer: H
Question 2
Answer: A
Question 3
Answer: E
Question 4
Answer: C
Question 5
Answer: A

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We still understand the effort, time, and money you will invest in preparing for your certification exam, which makes failure in the Google GCP-DE exam really painful and disappointing. Although we cannot reduce your pain and disappointment but we can certainly share with you the financial loss.

This means that if due to any reason you are not able to pass the GCP-DE actual exam even after using our product, we will reimburse the full amount you spent on our products. you just need to mail us your score report along with your account information to address listed below within 7 days after your unqualified certificate came out.

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