Product Manager, Data

Siftwell Analytics is a fast-growing company that combines healthcare operator expertise and artificial intelligence to provide insights for managed care health plans. The Product Manager, Data will own the data layer and be responsible for defining how health plan data is integrated within the platform, ensuring data quality, and collaborating with clients and engineering teams to enhance product capabilities.

Responsibilities:

• Lead technical data discussions with health plan clients to understand data environments and define how client data should map to Siftwell’s platform
• Serve as the primary technical counterpart in client onboarding meetings alongside Customer Success, using deep familiarity with healthcare data standards (EDI 834/837, claims, eligibility, clinical data) to guide productive discussions
• Evaluate client data delivery approaches and guide clients toward formats that align with Siftwell’s platform data model
• Build and maintain a standardized onboarding data playbook defining required data formats, field mappings, and delivery expectations for new clients
• Identify data availability gaps early and work with clients and internal teams to define workarounds or phased implementation approaches
• Own Siftwell’s data model roadmap, including the gold-layer schema, condition classification mappings (e.g., AHRQ CCSR), population definitions, and derived metrics
• Define and maintain canonical data specifications that translate healthcare domain knowledge into engineering-ready documentation for areas such as condition mapping, cost calculation logic, quality measure dependencies, and eligibility processing
• Define specifications for new data capabilities as the platform expands into additional healthcare domains (e.g., foster care, D-SNP, behavioral health), including relevant regulatory and definitional requirements
• Define data quality, governance, and validation frameworks that incorporate domain-informed validation of clinical and operational logic
• Write PRDs and technical specifications for data model changes, new data integrations, and pipeline enhancements
• Operate in a pod structure with the data engineering team, owning prioritization and specifications while engineering owns execution and architecture
• Partner with Product leadership to ensure data model decisions align with overall platform strategy and roadmap priorities
• Collaborate with Customer Success to distinguish between onboarding tasks, product feature requests, and out-of-scope client requests
• Translate patterns observed across client onboardings into product improvements — turning recurring bespoke work into repeatable platform capabilities
• Communicate data architecture decisions and onboarding requirements clearly to both technical and non-technical stakeholders, including client executives