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 17, 2026

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Question 1

A data pipeline uses Cloud Pub/Sub for ingesting data. The data is stored in topics and a Dataflow workflow reads from a subscription to that topic, processes the data, and writes output to BigQuery. What is the recommended way to authenticate when reading data from Cloud Pub/Sub?

A : Custom role

B : Google Workspace Identity

C : Use service accounts

D : Basic role

Answer: C

Question 2

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 : troduce data compression for each file to increase the rate file of file transfer.

B : ntact your internet service provider (ISP) to increase your maximum bandwidth to at least 100 Mbps.

C : design the data ingestion process to use gsutil tool to send the CSV files to a storage bucket in parallel.

D : emble 1,000 files into a tape archive (TAR) file. Transmit the TAR files instead, and disassemble the CSV files in the cloud upon receiving them.

E : eate 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.

Answer: A

Question 3

Which of these statements about exporting data from BigQuery is false?

A : export more than 1 GB of data, you need to put a wildcard in the destination filename.

B : only supported export destination is Google Cloud Storage.

C : ta can only be exported in JSON or Avro format.

D : only compression option available is GZIP.

Answer: C

Question 4

You are designing storage for very large text files for a data pipeline on Google Cloud. You want to support ANSI SQL queries. You also want to support compression and parallel load from the input locations using Google recommended practices. What should you do?

A : ansform text files to compressed Avro using Cloud Dataflow. Use BigQuery for storage and query.

B : ansform text files to compressed Avro using Cloud Dataflow. Use Cloud Storage and BigQuery permanent linked tables for query.

C : mpress text files to gzip using the Grid Computing Tools. Use BigQuery for storage and query.

D : mpress text files to gzip using the Grid Computing Tools. Use Cloud Storage, and then import into Cloud Bigtable for query.

Answer: D

Question 5

Which of the following is NOT a valid use case to select HDD (hard disk drives) as the storage for Google Cloud Bigtable?

A : u expect to store at least 10 TB of data.

B : u will mostly run batch workloads with scans and writes, rather than frequently executing random reads of a small number of rows.

C : u need to integrate with Google BigQuery.

D : u will not use the data to back a user-facing or latency-sensitive application.

Answer: C

Page: 1 / 95

Total 472 Questions | Updated On: Sep 17, 2026

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