Test Data Manager

This role is part of a horizontal data platform team, responsible for designing and delivering a federated testing platform for vertical delivery teams. The Test Data Manager will define standards, patterns, tooling, and reference implementations to enable teams to validate data products and services, prevent regressions, and produce auditable evidence of trust.

The focus is on building a self-service "testing-as-a-product" capability, collaborating with offshore engineers, and partnering with vertical teams to drive adoption and scale. Key outcomes A self-service testing platform with reusable test frameworks, CI/CD templates, and test data services.

Reference implementations for unit, integration, end-to-end, and performance tests. Centralized dashboards for test results, coverage, and quality metrics. Onboarding and enablement of vertical teams to adopt the platform.

Measurable improvements in defect rates, release readiness, and quality gate enforcement. Responsibilities Define federated test strategy, standards, and governance. Design and deliver the testing platform, including test frameworks, test data services, and observability tools.

Provide SDKs and templates for consistent test authoring. Partner with teams to bootstrap test coverage and establish shift-left practices. Deliver synthetic data generation, environment orchestration, and dependency virtualization.

Centralize test results and provide traceability for stakeholders. Lead offshore engineers and collaborate with cross-functional teams. 10+ years in software quality engineering/test automation, with 3–5 years in testing platforms or developer enablement.

Experience in data platforms and data product testing. Strong automation skills in Python or Java with CI/CD integration. Proven experience establishing federated quality practices. Preferred qualifications Familiarity with data testing tools (e.g., Great Expectations, Soda), API testing, and performance testing tools.

Experience with data platforms (e.g., Snowflake, Spark, Kafka) and cloud/DevOps tools (e.g., AWS, Kubernetes).

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