Product Manager, Data

Siftwell Analytics•Charlotte, NC

10d•Remote

About The Position

The Product Manager, Data owns the data layer as a product surface area at Siftwell and is responsible for defining how health plan data enters, maps to, and is represented within the platform. This role ensures that client data is translated into clear, consistent product logic that powers Siftwell’s analytics and operational workflows. This role sits at the intersection of client engagement, product development, and data engineering. The Product Manager, Data works directly with health plan clients to understand their data environments, align how their data should be structured and applied within Siftwell’s platform, and partner with engineering to translate those requirements into scalable product capabilities. Internally, this person owns the data product roadmap across the client lifecycle: defining Siftwell’s canonical data model, building repeatable onboarding and implementation specifications, establishing data quality standards, and translating healthcare domain knowledge into engineering-ready specifications as the platform evolves. Successful candidates for this role are comfortable moving between client conversations and technical product decisions. They are able to reason through messy healthcare data environments, identify the logic behind how data should support real operational workflows, and translate those insights into clear product specifications that scale across customers. This role reports to the Head of Product and may require occasional travel for client engagement and team collaboration. All new hires are subject to a one-time drug screening in accordance with Siftwell’s PHI compliance policies.

Requirements

6+ years of experience in healthcare data, analytics, implementation, or related roles within healthcare technology, analytics, or payer organizations.
Strong knowledge of healthcare data standards and file types, including EDI 834/837 transactions, claims, eligibility, and clinical datasets.
Experience leading client-facing technical discussions during implementation, onboarding, or data integration engagements.
Hands-on experience analyzing healthcare datasets using SQL, Python, or Excel and translating insights into data specifications, models, or mapping requirements for engineering teams.
Experience defining how external client data maps to internal platform data models, including field mappings, transformation logic, and validation requirements.
Familiarity with healthcare quality and operational concepts such as HEDIS, population health, risk adjustment, or medical economics.
Strong product judgment with the ability to distinguish one-off client requests from scalable platform solutions.

Nice To Haves

Experience at a healthcare SaaS company, population health vendor, or payer-facing analytics organization.
Familiarity with healthcare classification systems such as AHRQ CCSR, ICD-10, CPT/HCPCS, or CMS specifications.
Experience working with Medicaid, Medicare, or Marketplace health plan data environments.
Experience building repeatable onboarding processes, data playbooks, or implementation frameworks.

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.