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Senior, niche SDET/Data Platform role reduces applicant density despite metro location.
Requires specialized data engineering SDET and platform testing experience, limiting cross-industry transferability.
Mandatory 8+ years SDET experience for data platform and technical test automation makes shortlisting strict.
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Own end-to-end quality assurance for data products on the Enterprise Data Platform, ensuring data correctness, completeness, consistency, freshness, and lineage.
Design and implement automated testing and validation frameworks for data pipelines, transformations, APIs, and AI-powered Analytics Agent capabilities including user intent validation and response accuracy.
Drive root cause analysis for production data quality issues and define data quality metrics and monitoring to detect anomalies preemptively.
8+ years experience as Software Development Test Engineer (SDET) focused on Data Engineering and Data Platforms.
Experience designing and implementing automated testing frameworks for large-scale data pipelines and AI/ML data products.
Proven ability to validate data correctness and build reconciliation frameworks comparing Data Lake outputs to source systems.
Work Experience Required: 8+ years in SDET role specifically for data platforms and data engineering.
Deep understanding of enterprise data models, business domains, and complex data flows in large-scale data platforms.
Hands-on experience validating AI-generated insights and user intent for AI-powered analytics products.
Experience partnering across product, engineering, analytics, and AI teams to define robust validation strategies and drive quality engineering best practices.