Senior Software Engineer, Backend (Lake Analytics Platform)

Affirm exists to give people a clear, predictable way to pay over time, with no hidden fees or surprises. The Senior Software Engineer will build, operate, and extend platform capabilities for Affirm's data infrastructure, enabling reliable, secure, and self-service data applications at scale. The role focuses on platform reliability, data access and governance, observability, integrations, and emerging semantic layer and AI-native data tooling.

Responsibilities:

• 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 tooling to make them self-service for platform users, eliminating manual admin work
• Improve observability and incident response: Build telemetry, alerting, and log infrastructure so platform teams and application owners can diagnose and resolve issues independently. Establish runbooks and operational patterns that reduce blast radius and recovery time
• Support platform operations: Participate in on-call coverage, triage production incidents across platform services and the applications that run on them, and execute platform-level maintenance with care for the engineers and workflows that depend on the platform
• Contribute to the emerging platform roadmap: Help design and build next-generation platform capabilities — semantic layer infrastructure, agentic application patterns, and AI-native data tooling — as the platform grows to support Affirm's most ambitious data use cases
• Raise the engineering bar: Set and hold high standards in code review, design, operational readiness, and incident follow-through. Help establish patterns that other contributors can follow and build on

Requirements:

• Hands-on experience operating a cloud analytical data platform (e.g., Snowflake, Databricks, BigQuery, or similar), including access control design, data masking and governance, compute management, and cost optimization. You're comfortable operating with elevated privileges and understand the governance and blast-radius implications of each action
• Experience building and operating containerized applications — Docker image management, CI/CD pipeline design (Buildkite, GitHub Actions, or similar), deployment automation, and rollout practices for production services
• Experience building internal platforms, developer tooling, or self-service infrastructure that makes other engineers more productive. You design for the developer experience end-to-end, not just the happy path
• Comfort building integrations between systems — REST APIs, OAuth/OIDC, webhook ingestion, secrets management, egress networking configuration, and identity/SSO patterns in a managed cloud environment
• Proficiency in Python and SQL for building reliable, maintainable platform services. You write code that your teammates can own, not just code that works today
• Strong operational instincts — you instrument your systems, write runbooks, own your alerts, and treat on-call burden as a design constraint from day one. You close the loop on incidents with root cause analysis and durable fixes
• Familiarity with or interest in semantic layer design, LLM-integrated platform workflows, and agentic data tools. Curiosity about where data infrastructure and AI tooling intersect matters here
• Strong written and verbal communication. You're effective working across application teams, security, infrastructure, and platform users to scope, prioritize, and deliver — especially when requirements are ambiguous
• This position requires either equivalent practical experience or a Bachelor's degree in a related field