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Senior-level and niche GCP/data-pipeline QA skills reduce applicants but remain moderately competitive.
Specialized GCP BigQuery/Dataflow QA and cloud security focus limits cross-industry transferability.
Requires senior QA with GCP/data pipeline expertise and a Bachelor's degree, creating moderate filtering.
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Lead end-to-end QA for legacy-to-GCP migration, validating data pipelines, APIs, and cloud workflows across multiple GCP services.
Design and execute functional, data, and regression test suites ensuring 100% data completeness, schema accuracy, and transformation validation in multi-layer ETL pipelines.
Perform GCP security and IAM compliance validation; collaborate with engineering and product teams in Agile to deliver QA sign-offs, defect trend analysis, and release-readiness reports.
Bachelor’s Degree in Computer Science, Computer Engineering, Software Engineering, or Information Technology is mandatory.
Experience with QA processes for data pipelines, cloud workflows, and ETL migrations on GCP stack (BigQuery, GCS, Pub/Sub, Cloud SQL, Dataflow).
Proficient in automation using Python, BigQuery SQL, and CI/CD pipelines for data validation and reconciliation.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in cloud data pipeline QA with strong focus on GCP services and multi-layer ETL validation.
Familiar with security/IAM validation practices for cloud compliance and governance.
Skilled in automation and leveraging AI tools to optimize QA test case creation and defect triage within Agile development cycles.