Google Data Engineer Practice Exam
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Start NowAbout the Google Data Engineer Certification
The Google Data Engineer certification is designed for professionals who design, construct, and maintain data processing systems and pipelines, enabling reliable data collection, transformation, and analysis in the cloud. As technology evolves and industry demands grow more complex; this credential validates your ability to apply real-world skills and knowledge using Google tools and frameworks. Earning the certification positions you as a trusted expert, capable of solving high-impact challenges and contributing to secure, scalable, and efficient systems.
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Test Your Knowledge of Google Data Engineer
Question #1
The company wants to build a real-time analytics pipeline.
What is the recommended solution?
A) Use managed streaming services and scalable data warehouses.
B) Only collect batch data.
C) Disable pipeline automation.
D) Ignore data latency.
Solution
Correct answers: A – Explanation:
Streaming/warehouses enable real-time analytics. Batch/disabling/ignoring delays insights.
Question #2
The team must ensure data quality.
What is the best practice?
A) Implement validation, cleansing, and monitoring at every pipeline stage.
B) Only check data at the end.
C) Disable validation.
D) Ignore errors.
Solution
Correct answers: A – Explanation:
Validation/cleansing/monitoring ensure quality. End-only/disabling/ignoring misses issues.
Question #3
The business wants to keep costs low for large datasets.
What should be done?
A) Use tiered storage and optimize data retention policies.
B) Store all data at highest tier.
C) Disable retention limits.
D) Ignore storage reports.
Solution
Correct answers: A – Explanation:
Tiered/retention saves money. High-tier/disabling/ignoring wastes resources.
Question #4
The company needs to automate ETL jobs.
What is a good approach?
A) Use managed orchestration tools with workflow scheduling.
B) Only run jobs manually.
C) Disable scheduling.
D) Ignore task dependencies.
Solution
Correct answers: A – Explanation:
Orchestration/scheduling automate ETL. Manual/disabling/ignoring is inefficient.
Question #5
The team must secure sensitive information.
What is the best practice?
A) Encrypt data in transit/at rest and use role-based access controls.
B) Store unencrypted data.
C) Disable access controls.
D) Ignore audit trails.
Solution
Correct answers: A – Explanation:
Encryption/RBAC secure data. Unencrypted/disabling/ignoring is risky.
Question #6
The business wants to democratize data access.
What should be done?
A) Build self-service data platforms with robust governance.
B) Give open access to all users.
C) Disable governance.
D) Ignore data privacy.
Solution
Correct answers: A – Explanation:
Self-service/governance balance access. Open/disabling/ignoring is unsafe.
Question #7
The company must monitor pipeline performance.
What’s the best solution?
A) Enable monitoring dashboards and set performance alerts.
B) Only review after failures.
C) Disable monitoring.
D) Ignore data latency.
Solution
Correct answers: A – Explanation:
Dashboards/alerts catch issues early. Failure-only/disabling/ignoring is reactive.
Question #8
The team wants to prevent data duplication.
What is the best approach?
A) Use unique keys, deduplication logic, and regular audits.
B) Only deduplicate after issues.
C) Disable checks.
D) Ignore duplicates.
Solution
Correct answers: A – Explanation:
Streaming/warehouses enable real-time analytics. Batch/disabling/ignoring delays insights.
Question #9
The business needs to support data science teams.
What should be provided?
A) Curated, up-to-date datasets and scalable compute resources.
B) Only provide raw logs.
C) Disable data sharing.
D) Ignore user needs.
Solution
Correct answers: A – Explanation:
Curated/scalable supports science. Raw/disabling/ignoring hinders use.
Question #10
The company must comply with data regulations.
What is the first step?
A) Tag sensitive data and enable compliance audits in the platform.
B) Only check after an incident.
C) Disable tagging.
D) Ignore regulations.
Solution
Correct answers: A – Explanation:
Tagging/audits ensure compliance. Incident-only/disabling/ignoring is inadequate.
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