Free Google Professional-Data-Engineer Exam Questions

Become Google Certified with updated Professional-Data-Engineer exam questions and correct answers

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Total 472 Questions | Updated On: Jan 28, 2026

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Question 1

A data analyst currently has the bigquery.dataViewer role and can successfully query a materialized view. They also want to be able to refresh the materialized view. You want to use a predefined role but not grant them any more permissions than needed to refresh the materialized view. What predefined role would you grant to the user?

A : bigquery.dataOwner

B : bigquery.admin

C : bigquery.dataEditor

D : bigquery.mvUpdater

Answer: C

Question 2

When using Cloud Data Fusion you receive an error that a Dataproc operation failed and the user is not authorized to act as a service account. What would you do to correct this problem?

A : Create a Cloud Dataproc cluster before starting Cloud Data Fusion.

B : Grant the Service Account User role to Cloud Data Fusion.

C : Grant the Service Account User role to Cloud Dataproc.

D : Ensure both Cloud Data Fusion and Cloud Dataproc are running in the same zone.

Answer: B

Question 3

You are designing a Dataflow pipeline for a batch processing job. You want to mitigate multiple zonal failures

at job submission time. What should you do?

A : Specify a worker region by using the —region flag.

B : Set the pipeline staging location as a regional Cloud Storage bucket.

C : Submit duplicate pipelines in two different zones by using the —zone flag.

D : Create an Eventarc trigger to resubmit the job in case of zonal failure when submitting the job.

Answer: A

Question 4

What are the minimum permissions needed for a service account used with Google Dataproc?

A : ecute to Google Cloud Storage; write to Google Cloud Logging

B : ite to Google Cloud Storage; read to Google Cloud Logging

C : ecute to Google Cloud Storage; execute to Google Cloud Logging

D : ad and write to Google Cloud Storage; write to Google Cloud Logging

Answer: D

Question 5

Your new customer has requested daily reports that show their net consumption of Google Cloud compute

resources and who used the resources. You need to quickly and efficiently generate these daily reports. What

should you do?

A : Do daily exports of Cloud Logging data to BigQuery. Create views filtering by project, log type, resource, and user.

B : Filter data in Cloud Logging by project, resource, and user; then export the data in CSV format.

C : Filter data in Cloud Logging by project, log type, resource, and user, then import the data into BigQuery.

D : Export Cloud Logging data to Cloud Storage in CSV format. Cleanse the data using Dataprep, filtering by project, resource, and user.

Answer: B

Page: 1 / 95

Total 472 Questions | Updated On: Jan 28, 2026

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