How You Will Contribute
- Design, implement, and maintain an automated and extensible testing framework for the data platform, including but not limited to:
- Unit testing for data transformations
- Integration testing across datasets, models, and platform components
- Regression testing for output consistency
- Schema and data contract validation
- Invariant testing for core business rules
- End-to-end pipeline testing
- Performance and scalability testing
- AI prompt regression testing
- AI evaluation testing
- Telemetry validation for AI and data systems
- Establish development-time safeguards to validate business logic and expected behavior prior to release.
- Contribute to quality standards, release criteria, and reliability practices for core data products and public-facing integrations.
- Partner with data engineering, analytics engineering, product, and AI/application teams to embed testing into development workflows.
- Identify structural quality gaps and recommend scalable solutions.
- Contribute to platform resilience planning, including disaster recovery and failover readiness.
- Document testing standards, practices, and reusable frameworks for cross-team adoption.
What You Will Bring
- 5+ years of experience in Data Engineering, DevOps, ML Ops, ML Engineering, Analytics Engineering, and/or Site Reliability Engineering.
- Experience designing or implementing automated testing frameworks for data pipelines, ETL/ELT systems, analytics platforms, or similar environments.
- Strong SQL skills and experience validating complex transformation logic.
- Experience with modern data platforms, orchestration tools, and data quality practices.
- Demonstrated ability to translate business rules into automated validations and testing coverage.
- Experience partnering with cross-functional stakeholders to improve engineering quality and release confidence.
- Experience with semantic-layer architectures and downstream BI or application consumption.
- Experience supporting public-facing or customer-facing data products.
- Familiarity with AI/LLM-enabled systems and related quality practices, including prompt regression testing or evaluation frameworks.
- Experience with observability or monitoring tools for data systems.
- Experience defining platform standards or leading quality initiatives across teams.
- Familiarity with disaster recovery, resilience, and failover planning for data platforms.
- Enthusiasm to contribute to Stand Together's vision and principled approach to solving problems, and a commitment to stewarding our culture, which champions values including transformation and innovation, entrepreneurialism, humility, and respect.
What We Offer
- Competitive benefits: Enjoy a 6% 401(k) match with immediate vesting, flexible time off, comprehensive health and dental plans, plus wellness and mental health support through Peloton and Talkspace.
- A meaningful career: Join a passionate community of over 1,300 employees dedicated to improving lives and driving innovative solutions to complex social challenges.
- Commitment to growth: Thrive in a non-hierarchical environment that empowers employees to discover, develop and apply their unique talents.
- Competitive compensation: Our approach rewards the value you create through competitive salaries and bonus opportunities, allowing you to share in the success you help drive.
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