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$ cat jobs/senior-product-manager-data-platform-arbitalhealth-90e50deaa5d1.json

Senior Product Manager, Data Platform

Arbitalhealth·Worldwide·Remote·senior
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Arbital Health is a rapidly growing healthcare technology and actuarial leader that centralizes, measures, and adjudicates value-based care contracts at scale. We enable payers and providers to design, measure, and execute value-based agreements with greater transparency, efficiency, and financial predictability. We invest in hiring high potential and humble individuals who thrive in fast-paced environments and can rapidly grow their responsibilities as we continue to accelerate our growth. We were co-founded by Brian Overstreet and Travis May (founder & former CEO of LiveRamp and Datavant, the two biggest data companies of the last 20 years), and are backed by Transformation Capital, Valtruis and other leading investors. In our first 2 years, Arbital Health has established itself as a trusted partner for over 40 payers, providers, and other stakeholders looking to navigate the complexities of risk-based contracting. We are seeking a Product Manager, Data Platform, to own the strategy, roadmap, and execution of Arbital’s data platform – the systems that ingest, process, configure, and serve healthcare claims and contract data for value-based care. You'll define how data flows across the platform – from raw client files through standardized processing, contract configuration, financial reporting, and AI consumption – and partner with engineering, actuarial, and implementation teams to make these systems scalable, configurable, and self-serve so non-engineers can drive day-to-day operations. This is a high-impact individual contributor role for someone who is equally comfortable writing a PRD and digging into a data schema. Responsibilities: Product Strategy & Roadmap Own the product roadmap for Arbital’s data pipeline platform, including ingestion, transformation, calculation, validation, audit trail, and AI consumption layers Define and prioritize pipeline capabilities based on client needs, implementation learnings, engineering constraints, and long-term platform s