Uber's Finance Data Platform team builds and operates the foundational data products that power Uber's financial and profitability insights. We produce trusted, reconciled, and scalable financial and performance metrics used across all of Uber’s Lines of Business (LOBs) and Products. Our datasets and metrics sit at the core of how Uber understands business performance today and plans for tomorrow: they support reporting, forecasting, profitability analyses, investment cases, and future capital allocation decisions. We partner closely with Finance, Accounting, FP&A, Product, Data, and Operations teams to ensure stakeholders have a single source of truth for financial and profitability performance.

About the Role

As an Application Developer 1 / Data Analyst 1 (L3) on the Finance Data Platform team, you will help shape how Uber measures and understands business performance and profitability. Working closely with senior analysts, PMs, and Finance partners, you will contribute to the development of key financial and profitability metrics, build reporting and analytical views, and deliver high-quality analyses that support strategic decisions and capital allocation across Uber. You will grow into a trusted partner to Finance and Product stakeholders, translating financial and operational data into clear, structured insights and helping ensure that decisions are anchored on accurate, consistent metrics. You will also contribute to GenAI-powered self-serve tools that make Finance Data Platform data more accessible to internal customers.

What You'll Do

Support Finance, FP&A, Accounting, Product, and Data teams by building queries, reports, and dashboards that explain how Uber measures revenue, costs, margins, and profitability across LOBs, products, and geographies.
Help maintain and document core financial and profitability metric definitions (e.g., revenue, variable cost, contribution margin, unit economics) and ensure they are correctly applied in analyses and dashboards.
Build and maintain dashboards and recurring reports using existing curated data models and views to provide a single source of truth for business performance analyses and financial reporting.
Analyze large-scale financial and operational datasets to identify trends, drivers, and anomalies in revenue, cost, profitability, and efficiency, and summarize findings in a clear, structured way.
Provide analyses and data extracts that feed into strategic planning and capital allocation discussions, under the guidance of senior team members.
Partner with Finance and Product teams to define and track KPIs for products, features, and business initiatives, ensuring that performance is measured consistently over time.
Collaborate with data engineers and finance stakeholders to flag data quality issues, contribute to validation checks, and support reconciliation between financial systems and analytical datasets.
Contribute to GenAI-powered self-serve analytics tools (e.g., natural-language query interfaces, chat-based explainers, curated FAQs) that help internal customers quickly get answers and explanations from Finance Data Platform metrics.
Communicate analytical approach, assumptions, and results clearly to technical and non-technical audiences.

Basic Qualifications

2–4+ years of experience in an analytics-focused role (e.g., Data Analyst, BI Analyst, Product Analyst, or similar) working with data to support business decisions.
Strong proficiency in SQL, including experience querying large datasets and writing efficient, well-structured queries.
Experience with at least one scripting or analysis language such as Python or R for data analysis, automation, or data quality checks.
Experience building dashboards or reports in a modern BI tool (e.g., Tableau, Looker, Power BI).
Ability to break down ambiguous problems into clear analytical steps and deliver high-quality, accurate results.
Strong communication skills, with the ability to present data and findings in a clear, organized way to non-technical stakeholders.
Demonstrated curiosity about how businesses make money and how financial and operational metrics tie together.

Preferred Qualifications

Exposure to fintech, financial services, or experience working with Finance, FP&A, or Accounting teams in a data or analytics capacity.
Exposure to financial concepts such as revenue recognition, cost allocation, unit economics, contribution margin, forecasting, or capital allocation.
Experience working with financial or transactional datasets and an understanding of how they flow from source systems (e.g., billing, payments, ledgers, ERP) into analytical layers.
Experience supporting planning, forecasting, or performance management processes with data and metrics.
Interest or some exposure to using GenAI/LLMs for analytics or self-serve data access (e.g., prompt design, building prototypes, or working with natural-language query tools).