Finance Data Lead

What You’ll Be Doing

• Own financial data workflows end-to-end — from sourcing and transforming raw data (SQL, Python, etc.) to building clean, auditable outputs in Excel or BI tools
• Build and maintain financial models and dashboards that track key metrics such as origination volumes, revenue run rates, and portfolio performance
• Respond to ad hoc data requests from Finance, Product, and GTM — quickly, accurately, and with clear documentation
• Leverage AI tools (e.g., Claude, ChatGPT, Copilot) to accelerate analysis, automate repetitive tasks, and surface insights faster
• Partner with Engineering and Data teams to ensure financial data is correctly structured, accessible, and well-governed
• Maintain data integrity standards — building in checks, reconciliation logic, and clear audit trails across all financial outputs
• Support external reporting needs, including materials for investors, lenders, and board-level stakeholders

What We’re Searching For

Must-Haves

• 4–7 years of experience in a data-heavy role (data analyst, analytics engineer, financial analyst with strong technical depth, etc.)
• Expert-level Excel/Google Sheets skills (complex models, dynamic arrays, pivot tables)
• Strong SQL skills — you can write and optimize queries against large datasets independently
• Hands-on experience with modern AI tools and a genuine curiosity about how to apply them to financial workflows
• Baseline fluency in corporate finance concepts such as EBITDA, working capital, and structured finance
• High degree of trust and discretion — you'll have access to sensitive financial data and are expected to handle it responsibly
• Strong verbal communication skills — you can translate complex datasets into clear, concise narratives

Nice-to-Haves

• Experience in fintech, lending, or structured finance (familiarity with loan tapes, origination data, or SPV structures is a plus)
• Proficiency in Python or R for data manipulation and automation
• Experience with a BI tool (Looker, Tableau, Mode, etc.)
• Exposure to DBT, Airflow, or similar data pipeline tooling

Why This Role

• High-impact, high-visibility work — your outputs are presented in executive and investor materials
• A seat at the table for data infrastructure decisions within the Finance team
• Opportunity to define processes and tooling in a fast-moving environment
• Collaborative team that values rigor, speed, and intellectual curiosity