Finance Data Product Analyst — FP&A

It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at Intuitive . As a global leader in robotic-assisted surgery and minimally invasive care , our technologies—like the da Vinci surgical system and Ion —have transformed how care is delivered for millions of patients worldwide.

We’re a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human. Every day, our work helps care teams perform with greater precision and patients recover faster, improving outcomes around the world.

The problems we solve demand creativity, rigor, and collaboration. The work is challenging, but deeply meaningful—because every improvement we make has the potential to change a life.

If you’re ready to contribute to something bigger than yourself and help transform the future of healthcare , you’ll find your purpose here.

Primary Function of Position

The Finance Data Product Analyst will serve as the dedicated FP&A analytics support resource, owning the requirements-to-handoff lifecycle across core FP&A domains. This role fills a current gap where FP&A requirements gathering, stakeholder coordination, and AI-to-engineering handoff are absorbed across leads without dedicated capacity. The analyst will ensure faster turnaround, stronger domain ownership across GLTD, Revenue, CapEx, and HC portfolios, and less rework in downstream deliverables.

Roles and Responsibilities

Serve as the dedicated FP&A analyst for requirements intake — gather, clarify, document, and prioritize business requirements from Finance stakeholders across GLTD, Revenue, CapEx, and HC portfolios.

Translate business requirements into structured technical specifications and data model requirements for handoff to the onsite senior analyst and engineering team.

Own the requirements-to-engineering handoff process — ensure specifications are complete, unambiguous, and validated before passing to development, reducing rework cycles.

Perform data validation, reconciliation, and UAT support — verify that delivered models and reports match business intent and source data.

Debug and trace data through existing EDW models to answer stakeholder questions, identify discrepancies, and document root causes for engineering resolution.

Coordinate between onsite and offshore teams — manage requirements backlogs, track delivery status, flag gaps or conflicts, and ensure timely handoff at each stage.

Maintain documentation: business requirements documents, data dictionaries, test cases, and process guides.

Support AI-augmented analytics adoption by articulating business needs that could benefit from AI/ML capabilities and translating them into actionable requirements.

Qualifications

Required Skills and Experience

4 years of experience in BI analysis, data product analysis, or finance analytics support roles.

Strong understanding of FP&A concepts — general ledger, revenue recognition, CapEx planning, headcount reporting, cost center hierarchies.

SQL proficiency for data investigation — ability to query, trace, and validate data across EDW layers (not expected to build pipelines).

Experience with requirements gathering, documentation, and business-to-technical translation.

Familiarity with Snowflake or similar cloud data platforms from an analyst/consumer perspective.

Experience with Tableau or similar BI tools for report validation and basic analysis.

Strong written and verbal communication — ability to write clear specs and coordinate across time zones with onsite teams.

Detail-oriented with a structured approach to tracking deliverables and handoff checklists.

Preferred Qualifications

SAP Finance or ERP data familiarity (GL, AP, AR, cost center structures).

Exposure to AI/ML concepts — enough to recognize where AI-assisted analytics could add value to FP&A workflows.

Experience working in offshore delivery models with structured SDLC or agile processes.

Knowledge of data governance and data quality practices.

Required Education and Training

Bachelor's degree in finance, computer science, mathematics, information systems, or business.