Senior Product Manager, Analytics & Data Platforms

Bellese is seeking a Senior Product Manager to lead product strategy and delivery within a complex, data-intensive environment supporting federal healthcare programs. This role owns end-to-end product outcomes across analytics, data pipelines, and reporting systems.

You will operate as a senior, autonomous leader. You will drive clarity in an environment with legacy processes and high delivery pressure. You will partner closely with delivery teams and stakeholders to modernize workflows, reduce inefficiencies, and improve data quality and reliability.

This role requires strong product judgment and technical fluency in data systems. You must lead through ambiguity, identify systemic issues, and drive measurable improvements across teams and processes.

HQR

Our team is charged with maintaining and improving the software at the Centers for Medicare and Medicaid Services (CMS) that supports the Hospital Quality Reporting program. Thousands of hospitals across the country depend on these systems to submit quality measure data that reflects the care beneficiaries receive in their facility.  Our teams will continuously strive to modernize these systems, while improving them in ways that reduce provider burden and minimize costs to CMS.  We do this through HCD and Service design practices, product thinking, and skilled engineering.  At Bellese, we’re relentlessly focused on enabling and empowering providers to focus on improving the quality and safety of patient care.

• Own product direction across analytics, data pipelines, and reporting systems

• Define and execute a roadmap focused on scalability, data quality, and operational efficiency

• Identify and drive modernization opportunities across legacy analytics workflows and tooling

• Lead efforts to reduce manual processes, redundant validations, and siloed development

• Translate complex data workflows into clear product requirements and deliverables

• Partner with engineering to shape data models, ETL pipelines, and distributed processing systems

• Ensure data products meet standards for accuracy, performance, and reliability

• Drive improvements in data lineage, traceability, and documentation

• Work closely with data engineers on PySpark, Databricks, and distributed systems design

• Understand tradeoffs in data modeling, pipeline design, and performance optimization

• Contribute to decisions on architecture, tooling, and platform evolution

• Ensure alignment with cloud infrastructure, security, and governance requirements

• Lead backlog prioritization across competing data and reporting needs

• Balance short-term delivery with long-term system health

• Drive coordination across engineering, analytics, and reporting teams

• Ensure delivery meets timelines, quality expectations, and regulatory requirements

• Identify gaps in current team structure, workflows, and ownership models

• Drive integration of analytics work into core product teams to reduce silos and handoffs

• Establish clear ownership across calculations, data modeling, reporting, and delivery

• Improve team operating model to support predictable, scalable delivery

• Build trust across complex stakeholder groups including technical and non-technical partners

• Translate data concepts into clear business and program impact

• Proactively manage risks related to data accuracy, delivery, and dependencies

• Drive alignment across external partners and internal teams