Product Owner leading commercial data integration, modeling, and governance for McKesson’s healthcare business. Partnering with Canada’s Data & Analytics Hub and Commercial Intelligence team.
About the role
- Data Product Manager owning enterprise data products for Level Access, an accessibility technology company. Translating business needs into analytics, governance, and AI-enabled solutions.
Responsibilities
- Partner with business leaders to identify high-value data, analytics, automation, and AI opportunities
- Translate business objectives into a prioritized roadmap of reusable data products and capabilities
- Prioritize work based on business impact, operational efficiency, customer outcomes, AI readiness, and strategic goals
- Define success measures connecting data product delivery to business outcomes
- Define enterprise data domains, ownership models, business definitions, metrics, KPIs, and data contracts
- Maintain the enterprise data dictionary and business glossary
- Drive consistency across reporting, dashboards, operational systems, and AI-enabled workflows
- Advocate for data quality, lineage, governance, stewardship, and appropriate use of sensitive data
- Use rapid experimentation, AI-assisted prototyping, and iterative validation to shape data and AI product opportunities
- Translate business problems and data opportunities into product specifications for technical teams
- Use AI tools to accelerate discovery, requirements development, prototype generation, documentation, and decision support
- Establish a prototype-to-spec workflow for AI-augmented engineering teams
- Collaborate across product, data, AI, business systems, and engineering disciplines
- Partner with Data Engineers and Applied AI Engineers on solution design, prototype review, specification refinement, validation, testing, instrumentation, and adoption planning
- Ensure technical solutions align with business intent, data requirements, technical feasibility, governance expectations, and measurable outcomes
- Support an AI-augmented SDLC with AI-assisted specifications, test cases, implementation guidance, and documentation
- Drive adoption of trusted enterprise data products, faster delivery of insights and AI-enabled workflows, improved data quality and governance, and measurable business impact
Requirements
- 5+ years of experience in Product Management, Data Product Management, Business Systems, Analytics, or a related discipline
- Experience working with senior business stakeholders to define priorities, requirements, tradeoffs, and success measures
- Experience supporting AI, machine learning, copilots, agentic workflows, or intelligent automation
- Strong understanding of data platforms, reporting, BI, analytics, data governance, and enterprise data concepts
- Experience translating business needs into product specifications, technical requirements, user stories, acceptance criteria, and measurable outcomes
- Experience working in highly collaborative product and engineering environments that use rapid prototyping, iterative discovery, and early technical partnership
- Strong communication, facilitation, and stakeholder management skills
- Familiarity with AI-assisted product workflows, rapid prototyping, prompt-based experimentation, or AI-generated specification and documentation approaches
- Experience with modern data platforms such as Databricks, Snowflake, Microsoft Fabric, or equivalent
- Exposure to enterprise SaaS business models and operational metrics
Benefits
- Incentive compensation in the form of a company bonus plan
- Medical, dental, and vision insurance
- Life and disability coverage (STD/LTD)
- Retirement match
- Flexible paid time off
- Paid parental leave
- Remote work stipend
- Professional development reimbursement
- Benefits tailored to local regulations and employment status for employees in other locations
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