Senior Product Manager - Data Analytics & Reporting

About Highnote

Founded in 2020 by a team of leaders from Braintree, Pay Pal, and Lending Club, Highnote is an embedded finance company that sets the standard in modern card platform management. As an all-in-one card issuer processor and program management platform, we provide digital-first organizations with the flexibility to seamlessly issue and process payment cards, embed virtual and physical card payments, and integrate ledger and wallet functionalities—empowering businesses to drive growth and profitability.

We’ve raised $145M+ and have grown our team to 140+ employees. Headquartered in San Francisco, we’ve managed to build one of the most advanced payments teams in the industry, with team members in 25+ US states.

Operating through our core values of customer obsession, executional excellence, intentional inclusion, we’re helping businesses grow for the future by creating the payment products demanded by tomorrow, with the ability to solve for use cases that don’t exist yet.

We are fast-moving, hands-on, and strongly believe everyone deserves a seat at the table. We believe we’re unlocking incredible opportunities that can change the future of payments, as long as we have the right people to make it happen.

Highnote is seeking a Senior Product Manager - Data Reports & Analytics to lead the transformation of our financial intelligence and revenue operations. In this role, you will bridge the gap between raw transaction data and executive-level financial strategy. Your primary focus will be to build an automated, AI-driven Revenue Recognition Product that replaces manual/macros update overhead with scalable, verifiable software.

You will own the lifecycle of financial data - from discovery with Finance and Operations to the delivery of automated billing, invoicing, and reporting tools. You are someone who finds beauty in a complex spreadsheet but has the technical vision to turn that logic into a robust, AI-powered application that "just works."

• Lead the end-to-end development of a dedicated product for automated revenue recognition, ensuring every cent of Highnote’s complex flow is accounted for correctly.
• Codify manual finance spreadsheets (used for invoices and billing) into a scalable product. You will translate legacy formulas into production-grade logic.
• Partner with Data Science to develop an AI-driven application that mirrors and optimizes existing finance workflows, reducing manual intervention and identifying anomalies in billing patterns.
• Build rigorous validation and testing - creating and maintaining a comprehensive set of test cases to verify the correctness of billing logic. You will ensure that any change in business logic or data schema triggers automated verification to prevent financial regressions.
• Perform detailed discovery sessions with Finance, Operations, and Analytics Engineers to map out data dependencies and write high-fidelity PRDs for the development team.
• Define the metrics, calculations, and reporting UIs that support portfolio monitoring, financial audits, and regulatory reporting.
• Stakeholder Management, acting as the primary translator between the "language of finance" (accruals, deferrals, ledgers) and the "language of engineering" (APIs, schemas, latency).
• 8+ years of product management experience specifically in data reports, financial analytics, or revenue operations (Rev Ops).
• Strong foundation in accounting or financial operations; you must be comfortable auditing complex spreadsheets and converting them into technical requirements.
• Data Reporting Expertise; proven track record of building analytics products using SQL, BI tools (Looker/Tableau), and modern data warehouses (Snowflake/Big Query).
• Experience building "test-driven" products where data integrity and logic verification are at the forefront of the development lifecycle.
• Experience or strong interest in applying Machine Learning/GenAI to automate structured workflows and data matching.

• You have a background that spans both worlds (e.g., prior experience in Fintech, Investment Banking, or as a Data Engineer focused on Financial Systems).
• Experience…