Finance Data Lead

Parafin•San Francisco, CA

5d•Remote

About The Position

We're looking for a Finance Data Lead to sit at the intersection of finance and data engineering on our Finance team. This role requires someone who thinks in queries, models data pipelines, and moves quickly with modern tooling, while also being comfortable discussing a P&L or loan portfolio with senior leadership. You'll be the go-to person for turning raw financial data into clean, trusted, and actionable outputs — owning everything from ad hoc analyses to scalable reporting infrastructure.

Requirements

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

Responsibilities

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