Manager, Analytics Engineering (Finance Data)
Company: Affirm
Location: Las Vegas, NV (Remote)
Remote: Yes
Posted: 2026-01-31
About this role
Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.
Our Financial Systems team is looking for a Manager, Analytics Engineering to lead a team that turns complex finance data into reliable, governed, audit-ready reporting foundations. You will own end-to-end delivery of governed data models and the semantic layer that power reconciliations, close, and external reporting automation at Affirm. We're looking for someone who can lead, execute, and partner deeply across Accounting, Finance, and Data Engineering—operating as a hands-on technical leader to improve controls, data quality, and month-end outcomes at scale. The ideal candidate will deliver impact through scalable semantic layers and reporting solutions that elevate Finance function outcomes.
What You'll Do
- Lead end-to-end delivery of finance data models that support reconciliations, journal entry preparation, and close workflows, with a focus on reliability, controls, and audit readiness.
- Own the Financial Reporting semantic layer strategy and execution, including definition governance and adoption across reporting surfaces.
- Drive migration and modernization of reconciliation and close-support reporting into standardized, automated outputs where appropriate.
- Partner with Accounting and Finance stakeholders to translate close and audit requirements into durable data contracts, model specifications, and delivery roadmaps.
- Build and evolve reporting data products that make financial insights easy to consume and hard to misinterpret, partnering with BI and Financial Reporting tools (for example Sigma and Workiva).
- Build the foundations for AI-assisted finance analytics by enabling AI agents to safely access governed finance datasets (for example, through well-defined metrics, strong documentation, and permissioned datasets) to support self-service questions and report...