Google GCP-DE Questions & Answers - in .pdf
- Total Q&A: 77
- Update: Aug 25, 2026
- Price: $59.99
- Vendor: Google
- Exam Code: GCP-DE
- Exam Name: Data Engineer
- Features:
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- Complete Google Recommended Syllabus.
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- Exact Google GCP-DE Exam Questions with Correct Answers, verified by Experts with years of Experience in IT Field.
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Google GCP-DE Exam Syllabus Topics:
| Section | Weight | Objectives |
| Topic 1: Maintaining and optimizing data and ML solutions | 20% | - Security and governance
- 1. IAM and access control
- 2. Data encryption and compliance
- Machine learning integration
- 1. Vertex AI integration for pipelines
- 2. BigQuery ML usage
|
| Topic 2: Building and operationalizing data processing systems | 30% | - Data pipeline implementation
- 1. Dataflow pipeline development
- 2. Dataproc and Spark-based processing
- Data ingestion and transformation
- 1. ETL/ELT workflows
- 2. Pub/Sub streaming ingestion
|
| Topic 3: Designing data processing systems | 20% | - Data pipeline architecture design
- 1. Scalable data ingestion design
- 2. Batch vs streaming data processing selection
- Storage and data modeling
- 1. Data lake architecture on Google Cloud Storage
- 2. Data warehouse design using BigQuery
|
| Topic 4: Operationalizing data and ML pipelines | 30% | - Pipeline automation and orchestration
- 1. Cloud Composer workflows
- 2. Scheduling and monitoring pipelines
- Monitoring and troubleshooting
- 1. Logging and observability
- 2. Performance optimization and debugging
|
Google Data Engineer Sample Questions:
1. Which of these is not a supported method of putting data into a partitioned table?
A) Use ORDER BY to put a table's rows into chronological order and then change the table's type to "Partitioned".
B) If you have existing data in a separate file for each day, then create a partitioned table and upload each file into the appropriate partition.
C) Create a partitioned table and stream new records to it every day.
D) Run a query to get the records for a specific day from an existing table and for the destination table, specify a partitioned table ending with the day in the format "$YYYYMMDD".
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) Redesign the data ingestion process to use gsutil tool to send the CSV files to a storage bucket in parallel.
B) Introduce data compression for each file to increase the rate file of file transfer.
C) Transmit the TAR files instead, and disassemble the CSV files in the cloud upon receiving them.
D) 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.
E) Contact your internet service provider (ISP) to increase your maximum bandwidth to at least 100 Mbps.
F) Assemble 1,000 files into a tape archive (TAR) fil
3. 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 WHERE_PARTITIONTIME pseudo column
B) Use WHERE date BETWEEN YYYY-MM-DD AND YYYY-MM-DD
C) Use the TABLE_DATE_RANGE function
D) Use SELECT IF.(date >= YYYY-MM-DD AND date <= YYYY-MM-DD
4. You are designing storage for two relational tables that are part of a 10-TB database on Google Cloud. You want to support transactions that scale horizontally. You also want to optimize data for range queries on nonkey columns. What should you do?
A) Add secondary indexes to support query patterns.
B) Use Cloud SQL for storag
C) Use Cloud Dataflow to transform data to support query patterns.
D) Use Cloud Dataflow to transform data to support query patterns.
E) Use Cloud Spanner for storag
F) Use Cloud SQL for storag
G) Add secondary indexes to support query patterns.
H) Use Cloud Spanner for storag
5. When using Cloud Dataproc clusters, you can access the YARN web interface by configuring a browser to connect through a proxy.
A) HTTP
B) HTTPS
C) VPN
D) SOCKS
Solutions:
Question # 1 Answer: A | Question # 2 Answer: A,C | Question # 3 Answer: C | Question # 4 Answer: C | Question # 5 Answer: D |
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