Finance Data Product Analyst — FP&A

Intuitive•Peachtree Corners, GA

About The Position

The Finance Data Product Analyst provides dedicated FP&A analytics support and owns the requirements-to-handoff lifecycle across core FP&A domains. The role supports requirements gathering, stakeholder coordination, and handoff from business teams to engineering, with the goal of improving turnaround, domain ownership, and the quality of downstream deliverables across GLTD, Revenue, CapEx, and headcount portfolios. The analyst gathers and prioritizes Finance requirements, translates them into technical specifications and data model requirements, and validates specifications before development. The role also supports data validation, reconciliation, user acceptance testing, investigation of existing EDW models, coordination of delivery across onsite and offshore teams, and maintenance of requirements and process documentation. The analyst helps identify FP&A workflows that may benefit from AI- or ML-assisted analytics and translates those needs into actionable requirements.

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 data investigation, including querying, tracing, and validating data across EDW layers; pipeline development is not expected.
Experience gathering requirements, documenting them, and translating between business and technical teams.
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 writing clear specifications and coordinating 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 headcount 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 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 by managing requirements backlogs, tracking delivery status, flagging gaps or conflicts, and ensuring timely handoffs.
Maintain business requirements documents, data dictionaries, test cases, and process guides.
Articulate business needs that could benefit from AI/ML capabilities and translate them into actionable requirements.