Finance Data Product Analyst — FP&A
About The Position
The Finance Data Product Analyst serves as dedicated FP&A analytics support and owns the requirements-to-handoff lifecycle across core FP&A domains. The role provides dedicated capacity for FP&A requirements gathering, stakeholder coordination, and AI-to-engineering handoff, supporting faster turnaround, stronger domain ownership across GLTD, Revenue, CapEx, and HC portfolios, and less rework in downstream deliverables. The analyst gathers and prioritizes finance stakeholder requirements, translates them into technical specifications and data model requirements, and manages handoffs to onsite analysts and engineering teams. The role also validates data and deliverables, supports UAT, investigates data in existing EDW models, coordinates onsite and offshore delivery, maintains documentation, and identifies FP&A needs that may benefit from AI/ML capabilities.
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, querying, tracing, and validating data across EDW layers; building pipelines 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 HC portfolios.
- Translate business requirements into structured technical specifications and data model requirements for handoff to onsite senior analysts and engineering teams.
- Own the requirements-to-engineering handoff process, ensuring specifications are complete, unambiguous, and validated before development.
- Perform data validation and reconciliation, and support UAT 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 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.
Benefits
- Market-competitive compensation packages, including base pay, incentives, benefits, and equity.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
