Senior Staff Software Engineer, Backend (Data and Storage Services)

Affirm's engineering team is building a large-scale, highly-available, and global infrastructure that is shared across multiple financial products. Ensuring that our infrastructure is accessible to all engineers is critical to the success of the business. We pride ourselves on our culture across engineering of engaging in thorough technical design review, operational excellence, and capable incident response and analysis.

The Data and Storage Services team is responsible for handling all of Affirm's Data (OLAP and OLTP) requirements and encompasses the entire range from critical online checkout databases all the way to our Batch Orchestration, Streaming Infrastructure, Event Driven Frameworks, BI and analytics tools and systems. Our mission is to provide trustworthy, intuitive, and cost-efficient solutions for Affirmers to secure, store, analyze, and transform data at exceptional scale.

The Data Services organization encompasses the Lake Analytics Platform and Analytics Engineering teams. Our platform powers Affirm's analytical data ecosystem — from the lakehouse and query infrastructure that stores and serves data at scale, to the transformation and modeling layers that make data trustworthy and accessible to the business. We are responsible for Snowflake, FiveTran, Atlan, MonteCarlo, dbt, data governance, privacy controls, and the tooling that enables self-service analytics with an AI focused mindset across the company.

What you’ll do

As a member of the Data and Storage Services organization, you will collaborate with other teams — including Product, Infrastructure, Lakehouse Infra, Lakehouse Analytics and Analytics Engineering to:

• Architect and evolve Affirm's lakehouse analytics platform, driving strategy around Snowflake, Apache Iceberg, and Spark to deliver scalable, high-performance analytical infrastructure.

• Design and implement robust Role-Based Access Control (RBAC) and dynamic data masking policies in Snowflake, ensuring data access is secure, compliant, and auditable across the organization.

• Lead the technical direction of analytics engineering practices, including data modeling, transformation pipelines (dbt), and data quality frameworks that enable trustworthy, self-service analytics.

• Drive data governance and privacy engineering initiatives, leveraging tools like Atlan to manage data cataloging, lineage, classification, and policy enforcement.

• Identify and execute cost optimization strategies across Affirm's analytical compute and storage footprint, including Snowflake warehouse tuning, query optimization, and efficient data lifecycle management.

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