Staff Analytics Engineer, Subledger Platform

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.

About the Finance team

The Finance team ensures Affirm remains financially sound and strategically positioned for growth. Our team manages financial planning, accounting, pricing, vendor management, tax, investor relations, and corporate development. We deliver timely insights, accurate reporting, and careful analysis to support decision-making. From day-to-day financial operations to major investments, we enable sustainable, informed growth by maintaining strong fiscal discipline.

About the team

Financial Systems owns the data and reporting foundation for Accounting, and the operational reliability of the pipelines that power reporting, reconciliations, and automation. We are building and scaling a single source of truth for financial information using dbt and Snowflake to enable scalable BI, close workflows, controls, and automation across the org.

We’re looking for a Staff Analytics Engineer to build and own our Financial Subledger Data Platform —the canonical set of dbt models, governed datasets, and control frameworks that transform operational/ledger events into trusted, explainable, accounting-ready outputs. This is a senior hands-on role: you will write and ship production dbt code yourself (models, tests, docs), set standards for the platform, and directly manage and mentor one Analytics Engineer as a player/coach. This role operates with high autonomy and significant cross-functional partnership across Accounting, Financial Reporting, Financial Systems, and upstream product engineering teams.

We want someone who can maintain and harden today’s platform while also giving us flexibility to adopt new technologies (e.g., evolving warehouse patterns, new table formats, catalog/governance tooling, orchestration approaches) as our subledger and control needs scale.

What you’ll do

• Build and own dbt models for the financial subledger platform (staging → intermediate → canonical facts/balances/marts → semantic), including naming conventions, macros, and reusable patterns.
• Implement strong data quality and controls in dbt: tests (unit/relationship/assertions), freshness, anomaly checks, and automated reconciliations that support close and audit readiness.
• Embed AI-assisted reconciliation capabilities into the platform (within appropriate security/controls guardrails): automate variance triage, suggest likely root causes, and generate human-reviewable reconciliation narratives and evidence artifacts.
• Own end-to-end subledger data products (e.g., event/fact layers, balance rollforwards, reconciliation outputs) with traceability from source events through transformations to reporting outputs.
• Partner with Accounting/Financial Reporting to trans