Lead Financial Data Analyst
$145,000–$180,000 year
HybridWashington, District of Columbia, United States or District of Columbia, United States
Job Summary
Own the translation of large operational datasets into strategic financial frameworks by scaling data architecture, designing optimized Snowflake warehouses, and maintaining complex SQL and dbt models. Manage FP&A planning tools, automate revenue workflows for key metrics like CAC and LTV, and build self-service dashboards for executive leadership. Leverage Python and AI to improve forecasting for user cohorts and merchant retention, while partnering with product teams to model pricing impacts and evaluate M&A opportunities. This hybrid role sits at the intersection of FP&A and Data Engineering, requiring on-site attendance on Monday, Tuesday, and Thursday.
Required Qualifications
- 7+ years of experience in FP&A or Strategic Finance at a high-growth SaaS/Tech company
- Advanced SQL mastery (window functions, CTEs, query optimization)
- Experience with Snowflake, AWS, and HEX
- Experience using dbt for data transformation, or basic workflow orchestration with Airflow
- High proficiency in Python (Pandas, NumPy) and automating financial workflows
- Expert-level creation of dynamic reporting layers in Looker, HEX, and Pigment
- Advanced knowledge of unit economics (LTV, CAC, Payback Period, Churn) and corporate finance fundamentals
- In-office attendance on Monday, Tuesday, and Thursday
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