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: Sep 22, 2026

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Question 1

You are working on a sensitive project involving private user data. You have set up a project on Google Cloud Platform to house your work internally. An external consultant is going to assist with coding a complex transformation in a Google Cloud Dataflow pipeline for your project. How should you maintain users’ privacy?

A : ant the consultant the Viewer role on the project.

B : ant the consultant the Cloud Dataflow Developer role on the project.

C : eate a service account and allow the consultant to log on with it.

D : eate an anonymized sample of the data for the consultant to work with in a different project.

Answer: C

Question 2

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

A : ndows at every 100 MB of data

B : ngle, Global Window

C : ndows at every 1 minute

D : ndows at every 10 minutes

Answer: B

Question 3

Your company is running their first dynamic campaign, serving different offers by analyzing real-time data during the holiday season. The data scientists are collecting terabytes of data that rapidly grows every hour during their 30-day campaign. They are using Google Cloud Dataflow to preprocess the data and collect the feature (signals) data that is needed for the machine learning model in Google Cloud Bigtable. The team is observing suboptimal performance with reads and writes of their initial load of 10 TB of data. They want to improve this performance while minimizing cost. What should they do?

A : define the schema by evenly distributing reads and writes across the row space of the table.

B : performance issue should be resolved over time as the site of the BigDate cluster is increased.

C : design the schema to use a single row key to identify values that need to be updated frequently in the cluster.

D : design the schema to use row keys based on numeric IDs that increase sequentially per user viewing the offers.

Answer: A

Question 4

You are developing an Apache Beam pipeline to extract data from a Cloud SQL instance by using JdbclO.

You have two projects running in Google Cloud. The pipeline will be deployed and executed on Dataflow in

Project A. The Cloud SQL instance is running jn Project B and does not have a public IP address. After

deploying the pipeline, you noticed that the pipeline failed to extract data from the Cloud SQL instance due to

connection failure. You verified that VPC Service Controls and shared VPC are not in use in these projects.

You want to resolve this error while ensuring that the data does not go through the public internet. What

should you do?

A : Set up VPC Network Peering between Project A and Project B. Add a firewall rule to allow the peeredsubnet range to access all instances on the network.

B : Turn off the external IP addresses on the Dataflow worker. Enable Cloud NAT in Project A.

C : Set up VPC Network Peering between Project A and Project B. Create a Compute Engine instance without external IP address in Project B on the peered subnet to serve as a proxy server to the Cloud SQL database.

D : Add the external IP addresses of the Dataflow worker as authorized networks in the Cloud SOL instance.

Answer: C

Question 5

Which Cloud Dataflow / Beam feature should you use to aggregate data in an unbounded data source every hour based on the time when the data entered the pipeline?

A : hourly watermark

B : event time trigger

C : with Allowed Lateness method

D : processing time trigger

Answer: D

Page: 1 / 95

Total 472 Questions | Updated On: Sep 22, 2026

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