Senior Software Engineer (Backend, Lake Analytics Platform)
Company: Affirm
Location: Remote US
Salary: $173k - $255k per year
Type: Full-time
Posted: 2026-07-22
About this role
- The Data and Storage Services team is responsible for Affirm’s data infrastructure across OLTP and OLAP systems, spanning critical online checkout databases, batch orchestration, streaming infrastructure, event-driven frameworks, BI, analytics tooling, large-scale data platforms, and agentic data tools such as semantic layers and internal platform data applications
- Our mission is to provide trustworthy, intuitive, and cost-efficient solutions for Affirmers to secure, store, analyze, and transform data at exceptional scale
- This role focuses on the platform and applications layer of Affirm’s data infrastructure — building, operating, and extending systems that enable teams across Affirm to work with data at scale. You will be a core contributor to platform reliability, self-service capabilities, and the roadmap toward agentic data tooling and semantic layer infrastructure
- Build and operate core platform capabilities: Design and implement platform features that enable engineers across Affirm to build, deploy, and operate data applications at scale — covering automated provisioning, deploy pipelines, access control, service lifecycle management, and reliability tooling
- Develop integrations: Build and maintain integrations between the platform and internal systems — CI/CD pipelines, identity and secrets management, external APIs, and event-driven hooks — so that application teams have secure, reliable, and self-service access to the tools they need
- Strengthen data access and governance: Design and operate secure data access patterns across the platform’s analytical infrastructure, including RBAC, managed-access schemas, dynamic data masking, secure views, and cross-database grants that make platform data trustworthy without creating operational bottlenecks
- Automate toil and unlock self-service: Identify recurring support patterns — access provisioning, data pipeline failures, service health management, secrets management — and build the automation and tooli...