Principal Revenue Data Analyst, Toast

• Experience: 6–9+ years in data analytics, finance systems, or BI, preferably within fintech, payments, or high-volume e-commerce
• Technical Proficiency: Expert-level SQL skills and hands-on experience building analytical tables and views in Snowflake (or similar warehouses)
• Visualization: Proven ability to develop auditable, user-friendly dashboards in Sigma, Tableau, or comparable BI tools
• Financial Literacy: Solid understanding of financial concepts such as revenue flows, accruals, and balance sheet reconciliations
• Execution: Ability to operate independently as a high-level individual contributor, managing complex projects in an evolving environment
• The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture

Desirable

• As a member of the Revenue Accounting team, you will build the analytics and automation layer that moves Toast from manual spreadsheets toward system-driven controls and reconciliations
• This is a high-impact, hands-on role sitting at the intersection of Accounting, Finance Systems, and Data Engineering
• Data Modeling: You'll build and maintain event-based analytical tables in Snowflake (transactions, settlements, fees) to translate raw data into accounting-ready metrics
• BI & Reporting: Design and own self-service dashboards (Sigma/Tableau) used by Accounting to validate revenue, reconcile merchant payouts, and monitor variances
• Process Automation: Use tools like Alteryx or SQL to automate journal entry preparation and bank reconciliations, reducing manual effort and strengthening SOX controls
• Cross-Functional Partnership: Act as the "translator" between Accounting and Data Engineering, ensuring financial logic is accurately reflected in upstream data pipelines
• Data Governance: Partner with Internal Audit to ensure completeness and accuracy of finance data assets, maintaining documentation for SOX-relevant controls
• Strategic Ownership: Act as the primary owner of Finance analytics assets, proactively identifying ways to improve data quality and reporting efficiency