Free PDF 2026 Google Newest GCP-DE: Data Engineer Actual Test

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Google GCP-DE Exam Syllabus Topics:

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

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Google Data Engineer Sample Questions (Q47-Q52):

NEW QUESTION # 47
Which is not a valid reason for poor Cloud Bigtable performance?

Answer: B

Explanation:
The Cloud Bigtable cluster doesn't have enough nodes. If your Cloud Bigtable cluster is overloaded, adding more nodes can improve performance. Use the monitoring tools to check whether the cluster is overloaded.
Reference: https://cloud.google.com/bigtable/docs/performance


NEW QUESTION # 48
You are implementing several batch jobs that must be executed on a schedule. These jobs have many interdependent steps that must be executed in a specific order. Portions of the jobs involve executing shell scripts, running Hadoop jobs, and running queries in BigQuery. The jobs are expected to run for many minutes up to several hours. If the steps fail, they must be retried a fixed number of times. Which service should you use to manage the execution of these jobs?

Answer: B


NEW QUESTION # 49
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: D


NEW QUESTION # 50
By default, which of the following windowing behavior does Dataflow apply to unbounded data sets?

Answer: C

Explanation:
Dataflow's default windowing behavior is to assign all elements of a PCollection to a single, global window, even for unbounded PCollections Reference: https://cloud.google.com/dataflow/model/pcollection


NEW QUESTION # 51
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: A


NEW QUESTION # 52
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