Arbitalhealth is hiring a Senior Product Manager, Data Platform to join their Product team. Arbital Health is a rapidly growing healthcare technology and actuarial leader that centralizes, measures, and adjudicates value-based care contracts at scale. Key skills: Python, Go, AWS, AI, Data Science.
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 scalability goals
Translate complex healthcare data requirements from claims processing to VBC contract logic into structured, buildable product specs
Partner with leadership to align pipeline investments with Arbital’s broader product and go-to-market strategy
Execution & Delivery
Write detailed PRDs, user stories, and technical specifications for platform features, configurations, and automation tooling
Work directly with engineering to scope, sequence, and ship pipeline improvements — balancing speed, quality, and flexibility
Define acceptance criteria and lead QA processes for new pipeline & platform capabilities, ensuring outputs meet accuracy and performance standards
Drive platform delivery end-to-end, owning prioritization, cross-team dependencies, and release coordination
Data & Technical Depth
Develop deep fluency in Arbital’s data models, pipeline architecture, and healthcare data standards (claims, eligibility, attribution, CMS/ACO files), and actuarial concepts (IBNR, rebates, contract terms)
Work hands-on with data — running SQL queries, reviewing pipeline outputs, and validating logic — to inform product decisions and support debugging
Define standards for data quality, deduplication, business rule configuration, lineage, and pipeline observability across all client environments
Evaluate and recommend tooling improvements across the platform stack (e.g., Airflow, Databricks, AWS) in partnership with engineering
Cross-Functional Collaboration
Serve as the primary product owner for data capabilities across implementation, engineering, actuarial, and data science teams
Partner closely with the Implementation team to surface recurring client configuration needs and turn them into scalable platform features
Collaborate with actuarial and data science teams to ensure pipeline logic correctly supports attribution, aggregation, and actuarial use cases
Communicate roadmap priorities, tradeoffs, and delivery status clearly to both technical teams and non-technical stakeholders
4–7 years of experience in product management, with at least 2 years owning data platform, data infrastructure, data pipelines, or platform/API products
Strong technical foundation — comfortable reading data schemas, writing SQL, and engaging meaningfully with engineering on architecture decisions
Experience working with healthcare data (claims, eligibility, value-based care) strongly preferred
Proven ability to translate ambiguous, complex requirements into clear, actionable product specifications
Excellent cross-functional collaboration skills — experience working across engineering, data science, and client-facing teams
Strong written and verbal communication skills, with an ability to tailor messaging to both technical and business audiences
High attention to detail and a strong bias toward quality in data products
Comfortable operating with autonomy in a fast-moving, early-stage environment
Hands-on experience with Airflow, Databricks, Python, dbt, or AWS data services
Background in value-based care, actuarial modeling, or population health analytics
Experience building configurable, multi-tenant data pipelines at scale
Experience with data lineage, audit trail, or data governance products
Prior work at a health tech startup or data-driven healthcare company
Familiarity with BI tooling such as Sigma or Looker