Senior Data Product Manager (HealthCare)
Job Location: Denver, Colorado USA
Working Mode: Hybrid in-office (2-3 days in-office)
Experience: 8 to 15 Years
Employment Type: Full-time
Domain: HealthCare & Revenue cycle management Industry
About the role
We’re looking for a Senior Data Product Manager to help accelerate HealthCare transformation into a truly data-driven organization. In this role, you’ll define the strategy and execution
framework for how data is captured, structured, governed, and leveraged across our SaaS platform — ensuring that every product team and the business as a whole can rely on consistent, accurate, and actionable insights.
Your initial focus will be internal: partnering with product, engineering, operations, customer success, and finance to strengthen data quality, visibility, and alignment across teams. Over time, you’ll help shape how it uses data to power customer insights, automation, and AI-driven capabilities — turning information into a lasting competitive advantage.
This senior-level, cross-functional role blends product management, data strategy, and systems thinking. The ideal candidate brings both strategic vision and hands-on expertise to improve how data flows through the organization.
As a Data Product Manager, you’ll define how the company thinks about and uses data —building the foundation for smarter decisions, scalable growth, and future innovation.
What You’ll Do: Enable Data Across Products- Partner with Product Managers to define what success looks like for each product and feature — the metrics, instrumentation, and data requirements needed to measure
- Ensure data considerations are included in discovery, design, and delivery stages for all product initiatives.
- Collaborate closely with engineering and analytics to align event tracking, schema design, and system integrations.
- Build frameworks and best practices that improve how product teams plan, track, and learn from data.
- Act as a bridge between business, analytics, and technology teams to ensure the right data is available for decision-making. Strengthen Data Governance
- Establish consistent definitions and taxonomies for key product and business metrics.
- Partner with data engineering and analytics teams to improve data quality, completeness, and lineage
- Introduce standards for data documentation, ownership, and change management.
- Drive cross-functional adoption of shared data assets, dashboards, and tools.
- Promote a culture of data stewardship across teams. Drive Data-Driven Decision Making
- Create visibility into how products perform through reliable reporting and metrics dashboards.
- Work with operations, customer success, finance, and product leadership to ensure business decisions are informed by accurate, consistent data.
- Lead post-launch reviews and experimentation analysis to quantify impact and guide iteration towards adoption and optimized results.
- Identify opportunities to automate insight generation or embed analytics into the product experience.
Tasks
Prepare for Future Data Products & AI- Collaborate with product and engineering leaders to identify opportunities where data can enhance the customer experience through benchmarks, insights, or predictive recommendations.
- Develop a long-term vision for data and AI readiness, including the infrastructure, quality, and processes required to support intelligent features.
- Partner with design and engineering to prototype and validate data-powered capabilities that create measurable value.
Requirements
What You’ll Bring:
- 8–10 years of relevant experience in data analytics or data-intensive environments, including at least 3 years in a product management or data analytics leadership role.
- Demonstrated success collaborating with engineering, product, and business teams to define and deliver data-related initiatives.
- Strong understanding of data modeling, event tracking, and analytics instrumentation.
- Working knowledge of SQL and familiarity with modern data tools (dbt, Snowflake, Redshift, Power BI, Tableau, or similar).
- Excellent communication and stakeholder management skills — able to translate between technical and business perspectives.
- Proven ability to balance near-term operational improvements with long-term strategic vision.
- Experience working in Agile product development environments — comfortable defining stories, managing backlogs, and collaborating with teams through sprint cycles.
- Experience designing metric frameworks or governance programs at scale.
- Background in analytics, data science, or ETL, data platform product management.
- Familiarity with AI/ML data requirements and experimentation frameworks.
- Experience in healthcare, fintech, or other regulated industries (HIPAA, GDPR, SOC 2).
Benefits
Hybrid Model