Senior Product Manager, Data & Client Insights

The Senior Product Manager, Data & Client Insights owns the end-to-end data experience for clients, from the moment their data enters the platform to the moment it surfaces as a meaningful insight. On the integration side, this role defines the strategy and requirements for client data onboarding, working closely with Engineering and Implementation to reduce time-to-data and minimize onboarding friction. On the reporting side, the role owns the roadmap for the analytics and dashboards product, translating client needs into clear instrumentation requirements, report specs, and self-serve analytics capabilities.

This role is also the primary owner of the data architecture decisions the long-term platform vision depends on, defining the data contracts, identity mapping, and attribution methodology that make each tier of the outcome model defensible, and is responsible for the governance work that keeps those foundations synchronized as the platform and client base evolve. This includes establishing how AI-generated outputs are instrumented, classified, and treated as structured data inputs to the reporting layer.

• Define and own the strategy and requirements for client data onboarding, including HRIS connectors, CSV/API imports, LMS completion feeds, and SSO interoperability.
• Establish and maintain the minimal data contract standard — authoritative sources, required fields, delivery cadence, PII handling, SLAs, and identity mapping — and drive adoption of that standard across new and existing clients.
• Partner with Engineering and Implementation to reduce time-to-data, minimize onboarding friction, and build a repeatable integration motion that scales across the client base.
• Serve as the internal authority on how client data enters and flows through the platform, and the external point of contact for clients escalating data quality or integration issues

• Own the product roadmap for client-facing analytics and dashboards, translating client needs and CS feedback into clear instrumentation requirements, report specs, and self-serve analytics capabilities. This includes defining the requirements for AI-assisted insight delivery such as anomaly detection, automated narrative summaries, and natural language query interfaces as the reporting surface matures.
• Define and maintain data governance standards that ensure reporting outputs are accurate, performant, and actionable across the client base.
• Partner with internal stakeholders to prioritize reporting investments based on client feedback and to communicate the data platform roadmap to strategic accounts.

• Prioritize features and infrastructure investments based on client value, data quality impact, technical risk, and strategic fit with the long-term platform vision.
• Provide regular progress updates on roadmap initiatives to internal and external stakeholders, including executive sponsors and strategic clients.

• Communicate proactively and transparently with Engineering, CS, and leadership to align on data platform vision, strategy, priorities, and trade-offs.
• Serve as the unified, credible point of contact for clients on data questions — the person who can answer “why does my data look like this?” with full context spanning ingestion through reporting.
• Anticipate, prioritize, and resolve data quality escalations and reporting issues in partnership with Engineering, Support, and Customer Success.

• Deep data literacy: fluency in data modeling, pipeline concepts, and analytics instrumentation; SQL proficiency strongly preferred; experience with BI or reporting tools (e.g., Looker, Tableau).
• Familiarity with AI/ML concepts as they apply to data product work: how model outputs are instrumented and logged, how AI-generated signals are structured for downstream reporting, and how to define data contracts that account for probabilistic or scored outputs alongside deterministic event data.
• Demonstrated ability to define and govern data contracts, identity mapping, and attribution methodology in a B2B SaaS…