Vendor Expense Data Product (Finance)

Join us to lead high-visibility initiatives as a data product manager in Finance, focused on vendor and contract expense data and the associated forecasting processes. As a data product manager, you will set product strategy, support onboarding, and support users by managing an enhancement backlog and translating business needs into high-quality requirements and user stories. The successful candidate will partner closely with data modelers and engineering to design, build, and deploy data model changes that improve data accuracy, usability, and decision usefulness. Job Responsibilities Own the end-to-end product lifecycle for the vendor/contract expense data product, including vision, strategy, roadmap, and adoption. Lead user onboarding, enablement, and ongoing support to drive self-service usage and sustained adoption. Manage the enhancement backlog, including intake, prioritization, scope definition, dependency management, and release planning. Partner with data modelers and engineering to design, build, test, and deploy data model changes; ensure requirements are clear, feasible, and aligned to finance outcomes. Conduct analyses to identify data quality issues, process breakdowns, forecasting gaps, and opportunities for automation or improved controls; translate findings into actionable product work. Write user stories and related Agile artifacts (e.g., acceptance criteria) and maintain product documentation, including definitions, data lineage and assumptions, usage guidance, and process runbooks appropriate for finance and auditability needs. Deliver senior management "scorecard-style" updates, including concise reporting on adoption, data health, delivery progress, and impact against finance objectives. Required Qualifications, Capabilities, and Skills Experience in a data product management, financial analysis, or product management role. Experience with vendor/contract expense categories and forecasting processes is a plus. Strong analytical skills with a track record of identifying issues, diagnosing root causes, and driving resolution through structured problem-solving; experience leveraging modern tools and technical skills is a plus (e.g., Databricks SQL). Ability to translate business needs into clear requirements, user stories, and acceptance criteria, and to manage a prioritized backlog through delivery. Experience partnering with technical teams (data modelers, data engineers, BI developers) to deliver data model and reporting improvements. Ability to produce executive-ready communications, including concise, scorecard-style updates with clear status, risks, and decisions required. Experience supporting finance stakeholders with recurring operating rhythms (monthly close, forecast cycles, budget planning). Preferred Qualifications, Capabilities, and Skills Strategic thinking: Frames product direction around finance outcomes (forecast quality, transparency, control readiness, decision usefulness) and makes trade-offs explicitly. Micro-goal orientation and aggressive outcome pursuit: Breaks large objectives into measurable micro-goals, drives closure against timelines, and escalates early when risks emerge to maintain delivery momentum.

Analytical rigor:

Uses data to identify gaps and opportunities, validates hypotheses, and separates symptoms from root causes.

Stakeholder leadership:

Builds alignment across finance and technology, manages competing priorities, and communicates clearly to both technical and non-technical audiences.