About this role
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 Team:
We’re looking for an experienced, highly independent analytics engineer to join our Revenue Analytics team. This team owns the data products, reporting infrastructure, semantic foundations, and analytical systems that support Affirm’s Revenue organization.
About the Role: In this role, you will lead the development of scalable, trusted data products for Affirm’s revenue teams. You turn ambiguous business and technical problems into scalable solutions across data modeling, metrics, dashboards, automation, governance, and AI enablement. You will help set the technical direction for Revenue’s data layer, establish the semantic and metadata foundations required for AI, and raise the quality and impact of data across the Revenue organization.
What You’ll Do:
• Lead high-impact data product initiatives for Revenue, from ambiguous problem definition through technical design, implementation, rollout, and adoption.
• Advance AI initiatives within the Revenue data ecosystem by identifying high-value use cases, integrating AI into analytics engineering workflows, and establishing the semantic, metadata, context, quality, and evaluation foundations required for AI.
• Design and build durable, well-tested data products that power revenue operations, field and executive reporting, external merchant reporting, and analyst self-service.
• Set technical direction for Revenue’s data layer across dbt models, metrics, semantic structures, documentation, lineage, testing, governance, and access controls.
• Identify opportunities to simplify, automate, and scale Revenue Analytics through improved data architecture, tooling, governance, and enablement.
• Provide technical leadership and mentorship to analysts and cross-functional partners, raising the bar for how data products are designed, built, and maintained.
What We Look For:
• 7+ years of experience in analytics engineering, business intelligence, data engineering, data product development, or a related technical analytics role.
• Deep expertise in SQL, dbt, data modeling, metrics design, data quality, documentation, and modern analytics engineering practices.
• Strong working knowledge of BI tools such as Sigma, Looker, or Tableau, cloud data warehouses such as Snowflake, and modern data platforms such as Databricks.
• Strong understanding of the foundations required for reliable AI—including semantic layers, metadata, evaluations, documentation, lineage, access controls, and data quality—and experience applying AI tools within analytics engineering workflows.
• Demonstrated ability to independently lead complex, ambiguous projects by defining scope, sequencing work, managing tradeoffs, aligning stakeholders, and delivering durable technical solutions.
• Experience designing scalabl