Senior Staff Software Engineer, Backend (Data and Storage Services)
About the role
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.
Responsibilities
Architect and implement core components of Affirm's lakehouse analytics platform, with a focus on scalability, governance, and reliability.
Leverage deep knowledge of Snowflake to architect RBAC models, dynamic data masking, warehouse optimization, and multi-cluster compute strategies.
Drive the technical strategy for data modeling and transformation using dbt, including testing frameworks, documentation standards, and CI/CD for data pipelines.
Design and operate data governance frameworks using tools like Atlan, including data cataloging, lineage tracking, classification, and automated privacy 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.
Work closely with product engineering, data science, and business intelligence teams to translate business requirements into technical solutions, and with fellow engineers to deliver high-quality data infrastructure.
Tackle the challenges of large-scale analytical data systems, including Apache Iceberg table management, schema evolution, storage optimization, and integration with Spark and Snowflake.
Mentor engineers across the Lake Analytics Platform and Analytics Engineering teams, providing guidance on emerging technologies, development practices, and fostering a culture of technical excellence.
Participate in an on-call rotation and collaborate with other teams such as SRE to resolve production issues.
Qualifications
Experience: 10+ years of experience in software engineering or data engineering, with a proven track record of delivering complex data platform solutions that improve accessibility, performance, and governance of analytics infrastructure.
Snowflake Expertise: 6+ years of hands-on experience with Snowflake or comparable analytical data warehouses, including RBAC design, data masking, query optimization, and cost management.
Lakehouse & Big Data: Strong experience with Apache Iceberg, Spark, and cloud-native data lake architectures on AWS (S3, EKS).
Analytics Engineering: Experience with dbt or equivalent transformation frameworks, including data modeling best practices, testing, and CI/CD for data pipelines.
Problem Solving: Exceptional problem-solving and analytical skills, with the ability to identify and resolve complex technical challenges and establish long-lasting solutions and processes.
Programming Skills: Proficiency in Python and SQL, with a strong emphasis on clean, maintainable code. Experience with Kotlin or Go is a plus.
Leadership: Demonstrated leadership and mentorship skills, with the ability to inspire and guide others.