Data Product Manager

Accountabilities: Own and prioritize the enterprise data product roadmap by identifying high-value opportunities across data, analytics, automation, and AI, and aligning initiatives with business priorities and measurable outcomes. Partner with senior business stakeholders to define objectives, requirements, tradeoffs, success measures, and opportunities for reusable data products and capabilities. Establish trusted data domains by defining business definitions, ownership models, KPIs, metrics, data contracts, and governance practices while maintaining the enterprise data dictionary and business glossary. Promote consistent and responsible use of data across reporting, dashboards, operational systems, and AI-enabled workflows, with a focus on quality, lineage, governance, stewardship, and appropriate handling of sensitive information. Drive AI-augmented product development through rapid experimentation, AI-assisted prototyping, iterative validation, and the translation of business opportunities into actionable product specifications. Use AI tools to accelerate discovery, research, synthesis, requirements development, prototype creation, documentation, and decision support while ensuring outputs are validated through human expertise. Collaborate closely with Data Engineers, Applied AI Engineers, Business Systems, and other technical teams on solution design, prototype reviews, specification refinement, testing, instrumentation, and adoption planning. Ensure technical solutions remain aligned with business objectives, data requirements, technical feasibility, governance expectations, and measurable outcomes. Contribute to an AI-augmented software development lifecycle by helping create specifications, test cases, implementation guidance, and documentation that can be accelerated through AI-assisted workflows. Help establish repeatable processes that move validated prototypes and concepts into clear, actionable requirements for engineering teams. Requirements 5+ years of experience in Product Management, Data Product Management, Business Systems, Analytics, or a related discipline. Demonstrated experience partnering with senior business stakeholders to establish priorities, define requirements, evaluate tradeoffs, and establish measurable success criteria. Experience working with AI, machine learning, copilots, agentic workflows, intelligent automation, or related emerging technologies. Strong understanding of enterprise data platforms, business intelligence, reporting, analytics, data governance, and core data concepts. Proven ability to translate business needs into product specifications, technical requirements, user stories, acceptance criteria, and measurable business outcomes. Experience working collaboratively with product and engineering teams in environments that emphasize rapid prototyping, iterative discovery, and early technical collaboration. Strong communication, facilitation, stakeholder management, and cross-functional collaboration skills. Familiarity with AI-assisted product development, prompt-based experimentation, rapid prototyping, or AI-generated specifications and documentation is an asset. Experience with modern data platforms such as Databricks, Snowflake, Microsoft Fabric, or equivalent technologies is preferred. Exposure to enterprise SaaS business models and operational metrics is beneficial. Ability to balance strategic thinking with hands-on product discovery, prioritization, documentation, and delivery. Benefits Full-time remote position with a flexible work environment. Annual base salary of $92,000–$100,000 USD for employees located in the United States. Eligibility for incentive compensation through a company bonus plan. Medical, dental, and vision insurance. Life and short- and long-term disability coverage. Retirement plan with employer matching. Flexible paid time off. Paid parental leave. Remote work stipend. Professional development reimbursement. Benefits and employment support tailored to applicable local requirements for eligible employees. Opportunity to work on data, AI, and accessibility-focused initiatives with cross-functional teams.