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Google GCP-DE Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Designing data processing systems22%-27%- Designing data pipelines
  • 1. Design orchestration workflows
  • 2. Build ETL and ELT pipelines
  • 3. Optimize pipeline performance and cost
- Designing for data ingestion
  • 1. Select appropriate storage systems
  • 2. Design batch and streaming ingestion solutions
  • 3. Design scalable and reliable ingestion architecture
Topic 2: Building and operationalizing data processing systems28%-33%- Operationalizing systems
  • 1. Implement fault tolerance and recovery
  • 2. Manage logging and alerting
  • 3. Monitor data pipelines and workloads
- Building data processing systems
  • 1. Implement streaming data systems
  • 2. Use BigQuery, Dataflow, Pub/Sub, Dataproc and related services
  • 3. Implement batch processing systems
Topic 3: Managing and optimizing solutions20%-25%- Managing resources and costs
  • 1. Tune query and pipeline performance
  • 2. Optimize storage and compute usage
  • 3. Control operational costs
- Reliability and scalability
  • 1. Scale data workloads efficiently
  • 2. Implement disaster recovery strategies
  • 3. Design highly available systems
Topic 4: Ensuring solution quality20%-25%- Data quality management
  • 1. Validate and clean data
  • 2. Maintain metadata and lineage
  • 3. Implement data governance
- Security and compliance
  • 1. Manage IAM and access control
  • 2. Implement encryption and compliance controls
  • 3. Protect sensitive data

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Google GCP-DE Exam Questions For Greatest Achievement [Updated 2026]

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Google Data Engineer Sample Questions (Q26-Q31):

NEW QUESTION # 26
You want to automate execution of a multi-step data pipeline running on Google Cloud. The pipeline includes Cloud Dataproc and Cloud Dataflow jobs that have multiple dependencies on each other. You want to use managed services where possible, and the pipeline will run every day. Which tool should you use?

Answer: D


NEW QUESTION # 27
You want to process payment transactions in a point-of-sale application that will run on Google Cloud Platform. Your user base could grow exponentially, but you do not want to manage infrastructure scaling.
Which Google database service should you use?

Answer: C


NEW QUESTION # 28
You have historical data covering the last three years in BigQuery and a data pipeline that delivers new data to BigQuery daily. You have noticed that when the Data Science team runs a query filtered on a date column and limited to 30-90 days of data, the query scans the entire table. You also noticed that your bill is increasing more quickly than you expected. You want to resolve the issue as cost-effectively as possible while maintaining the ability to conduct SQL queries. What should you do?

Answer: E


NEW QUESTION # 29
You are selecting services to write and transform JSON messages from Cloud Pub/Sub to BigQuery for a data pipeline on Google Cloud. You want to minimize service costs. You also want to monitor and accommodate input data volume that will vary in size with minimal manual intervention. What should you do?

Answer: A


NEW QUESTION # 30
MJTelco needs you to create a schema in Google Bigtable that will allow for the historical analysis of the last 2 years of records. Each record that comes in is sent every 15 minutes, and contains a unique identifier of the device and a data record. The most common query is for all the data for a given device for a given day. Which schema should you use?

Answer: B


NEW QUESTION # 31
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