Senior Data Analyst

Primary Responsibilities

• Build Trusted Finance Data Products
• Build, enhance, and maintain Finance tables, views, transformations, pipelines, and analytical models within established enterprise architecture, security, development, and governance standards.
• Develop reusable data products supporting bookings, customers, billing, revenue, operational activity, and portfolio performance.
• Use SQL and Python to automate data preparation, validation, and analytical workflows, and convert repeatable analyses into scalable assets.
• Apply appropriate source control, testing, deployment, monitoring, and documentation practices to Finance data products.
• Partner, Validate, and Operationalize
• Translate FP&A and Portfolio Analytics needs into clear source requirements, data grain, business rules, transformation logic, quality controls, and acceptance criteria.
• Own Finance requirements, prioritization, validation, and acceptance for data products delivered in partnership with onshore and offshore Shared Data Services teams.
• Reconcile outputs to source systems, financial reporting, operational reporting, and approved methodologies; identify and resolve data quality issues, logic gaps, hierarchy problems, and incomplete coverage.
• Maintain documentation for metric definitions, data lineage, business rules, assumptions, and known limitations, and coordinate issue resolution through Finance sign-off.
• Deliver Advanced Analytics and Self-Service
• Use SQL, Python, and appropriate analytical methods to solve complex customer, revenue, pricing, forecasting, portfolio, and operational questions.
• Build semantic models, dashboards, and analytical tools using Power BI or a comparable enterprise business intelligence platform.
• Enable FP&A users to independently answer recurring business questions with trusted data, reducing manual extracts, spreadsheet-based preparation, and one-off reporting.
• Use approved AI-assisted development tools to improve coding, testing, documentation, and analytical productivity while validating outputs and protecting confidential data.