Staff Analytics Analyst (Full Stack, Revenue)

Role Overview

Join Affirm’s Revenue Analytics team as a Staff Analytics Analyst (Full Stack, Revenue). You will lead scalable data product development, advance AI initiatives in the Revenue data ecosystem, and set the technical direction for Revenue’s data layer—while mentoring analysts and partnering cross-functionally.

Key Missions / Responsibilities

• Lead scalable, trusted revenue data products: turn ambiguous business and technical problems into durable, scalable solutions.
• Advance AI initiatives within Revenue analytics by:
  • identifying high-value use cases
  • integrating AI into analytics engineering workflows
  • establishing foundations such as semantic layers, metadata, context, quality, and evaluation
• Provide technical leadership and mentorship to analysts and cross-functional partners, raising the bar for how data products are designed, built, and maintained.

Requirements

• Strong understanding of the foundations for reliable AI, including:
  • semantic layers, metadata, evaluations
  • documentation, lineage, access controls, data quality
  • experience applying AI tools in analytics engineering workflows
• Salesforce familiarity, supporting GTM/revenue/sales operations teams.
• Ability to independently lead complex, ambiguous projects: define scope, sequence work, manage tradeoffs, align stakeholders, deliver durable solutions.
• Experience designing scalable data products for multiple audiences and influencing both technical and non-technical stakeholders on architecture and product direction.
• Strong working knowledge of:
  • BI tools: Sigma, Looker, or Tableau
  • Cloud data warehouses: Snowflake
  • Modern data platforms: Databricks
  • Analytics engineering: modern practices for documentation and quality
• Deep expertise in SQL, dbt, data modeling, metrics design, data quality, documentation, and lineage.

Nice-to-Haves

• Not explicitly stated, but additional value in strong revenue analytics/data platform leadership and AI implementation experience in analytics engineering.

Experience

• 7+ years in analytics engineering, business intelligence, data engineering, data product development, or a related technical analytics role.