Google GCP-DE : Data Engineer

GCP-DE pass collection

Exam Code: GCP-DE

Exam Name: Data Engineer

Updated: Sep 06, 2026

Q & A: 77 Questions and Answers

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Google GCP-DE Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Operationalizing data and ML pipelines30%- Monitoring and troubleshooting
  • 1. Logging and observability
    • 2. Performance optimization and debugging
      - Pipeline automation and orchestration
      • 1. Cloud Composer workflows
        • 2. Scheduling and monitoring pipelines
          Topic 2: Designing data processing systems20%- Storage and data modeling
          • 1. Data lake architecture on Google Cloud Storage
            • 2. Data warehouse design using BigQuery
              - Data pipeline architecture design
              • 1. Batch vs streaming data processing selection
                • 2. Scalable data ingestion design
                  Topic 3: Building and operationalizing data processing systems30%- Data pipeline implementation
                  • 1. Dataflow pipeline development
                    • 2. Dataproc and Spark-based processing
                      - Data ingestion and transformation
                      • 1. Pub/Sub streaming ingestion
                        • 2. ETL/ELT workflows
                          Topic 4: Maintaining and optimizing data and ML solutions20%- Machine learning integration
                          • 1. BigQuery ML usage
                            • 2. Vertex AI integration for pipelines
                              - Security and governance
                              • 1. Data encryption and compliance
                                • 2. IAM and access control

                                  Google Data Engineer Sample Questions:

                                  Question 1

                                  You work for a large fast food restaurant chain with over 400,000 employees. You store employee information in Google BigQuery in a Users table consisting of a FirstName field and a LastName field. A member of IT is building an application and asks you to modify the schema and data in BigQuery so the application can query a FullName field consisting of the value of the FirstName field concatenated with a space, followed by the value of the LastName field for each employee. How can you make that data available while minimizing cost?

                                  A. Create a Google Cloud Dataflow job that queries BigQuery for the entire Users table, concatenates the FirstName value and LastName value for each user, and loads the proper values for FirstName, LastName, and FullName into a new table in BigQuery.
                                  B. Create a Google Cloud Dataproc job to process the CSV file and output a new CSV file containing the proper values for FirstName, LastName and FullNam G. Run a BigQuery load job to load the new CSV file into BigQuery.
                                  C. Add a new column called FullName to the Users tabl
                                  D. Run an UPDATE statement that updates the FullName column for each user with the concatenation of the FirstName and LastName values.
                                  E. Use BigQuery to export the data for the table to a CSV fil
                                  F. Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.


                                  Question 2

                                  Cloud Dataproc is a managed Apache Hadoop and Apache service.

                                  A. Spark
                                  B. Fire
                                  C. Ignite
                                  D. Blaze


                                  Question 3

                                  Which of the following job types are supported by Cloud Dataproc (select 3 answers)?

                                  A. Spark
                                  B. Hive
                                  C. YARN
                                  D. Pig


                                  Question 4

                                  You are designing the database schema for a machine learning-based food ordering service that will predict what users want to eat. Here is some of the information you need to store:
                                  The user profile: What the user likes and doesn't like to eat
                                  The user account information: Name, address, preferred meal times
                                  The order information: When orders are made, from where, to whom
                                  The database will be used to store all the transactional data of the product. You want to optimize the data schem a. Which Google Cloud Platform product should you use?

                                  A. Cloud Bigtable
                                  B. BigQuery
                                  C. Cloud Datastore
                                  D. Cloud SQL


                                  Question 5

                                  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. Use Cloud SQL for storag
                                  B. Add secondary indexes to support query patterns.
                                  C. Use Cloud Dataflow to transform data to support query patterns.
                                  D. Use Cloud Spanner for storag
                                  E. Use Cloud SQL for storag
                                  F. Use Cloud Dataflow to transform data to support query patterns.
                                  G. Add secondary indexes to support query patterns.
                                  H. Use Cloud Spanner for storag


                                  Solutions:

                                  Question 1
                                  Answer: D
                                  Question 2
                                  Answer: A
                                  Question 3
                                  Answer: A,B,D
                                  Question 4
                                  Answer: B
                                  Question 5
                                  Answer: C

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