Finance Data Product Analyst — FP&A
About The Position
The Finance Data Product Analyst serves as dedicated FP&A analytics support, owning the requirements-to-handoff lifecycle across GLTD, Revenue, CapEx, and HC portfolios. The role supports faster turnaround, stronger domain ownership, and reduced rework by coordinating requirements gathering, stakeholder collaboration, and handoffs from AI-related business needs to engineering. The analyst gathers and clarifies Finance stakeholder requirements, translates them into technical specifications and data-model requirements, and validates deliverables before and after development. The role also supports data investigation and reporting validation, coordinates onsite and offshore delivery teams, maintains project and process documentation, and helps identify FP&A workflows that could benefit from AI/ML capabilities.
Requirements
- 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 with requirements gathering, documentation, and business-to-technical translation.
- 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
- SAP Finance or ERP data familiarity, 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 validate specifications for completeness and clarity 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 onsite and offshore teams, manage requirements backlogs, track delivery status, flag gaps or conflicts, and ensure 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
