Finance Data Product Analyst — FP&A

Intuitive•Durham, NC

2h•$113,600 - $192,300•Onsite

About The Position

The Finance Data Product Analyst serves as dedicated FP&A analytics support, owning the requirements-to-handoff lifecycle across core FP&A domains. The role provides dedicated capacity for requirements gathering, stakeholder coordination, and AI-to-engineering handoff, supporting faster turnaround and stronger domain ownership across GLTD, Revenue, CapEx, and HC portfolios while reducing rework in downstream deliverables. The analyst gathers and clarifies Finance stakeholder needs, translates them into technical specifications and data model requirements, and ensures that requirements are complete and validated before engineering begins development. The position also supports data validation, reconciliation, user acceptance testing, investigation of existing EDW models, coordination across onsite and offshore teams, and adoption of AI-augmented analytics. The position is fully onsite and designated as a day shift. Compensation ranges vary by region: Region 1 is $133,700–$192,300, and Region 2 is $113,600–$163,500. The role may be filled at a different job level depending on business need and the selected candidate’s qualifications.

Requirements

At least 4 years of experience in BI analysis, data product analysis, or finance analytics support roles.
Strong understanding of FP&A concepts, including general ledger, revenue recognition, CapEx planning, headcount reporting, and cost center hierarchies.
SQL proficiency for investigating, tracing, and validating data across EDW layers; building pipelines is not expected.
Experience with requirements gathering, documentation, and translating business needs into technical specifications.
Familiarity with Snowflake or similar cloud data platforms from an analyst or consumer perspective.
Experience with Tableau or similar BI tools for report validation and basic analysis.
Strong written and verbal communication skills, including the ability to write clear specifications and coordinate across time zones with onsite teams.
Detail-oriented, structured approach to tracking deliverables and handoff checklists.
Bachelor's degree in finance, computer science, mathematics, information systems, or business.

Nice To Haves

Familiarity with SAP Finance or ERP data, including GL, AP, AR, and cost center structures.
Exposure to AI/ML concepts sufficient 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.

Responsibilities

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 and ensure specifications are complete, unambiguous, and validated before development.
Perform data validation, reconciliation, and UAT support to verify delivered models and reports against 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 by managing requirements backlogs, tracking delivery status, flagging gaps or conflicts, and ensuring timely handoff.
Maintain business requirements documents, data dictionaries, test cases, and process guides.
Support AI-augmented analytics adoption by identifying business needs that could benefit from AI/ML capabilities and translating them into actionable requirements.