Analytics Engineer (Revenue Analytics) 100% remote

Affirm operates in the financial services domain, reinventing credit to provide transparent buy now, pay later options without hidden fees or compounding interest. The role is within the Revenue Analytics team, responsible for building and maintaining data products and reporting infrastructure for Affirm's Revenue organization.

• 3+ years of experience in analytics engineering or business intelligence roles
• Strong working knowledge of SQL, dbt, Python, data modeling, and data visualization
• Hands-on experience with BI tools such as Sigma, Looker, or Tableau, Databricks, and cloud data warehouses like Snowflake
• Understanding of data foundations necessary for reliable AI, including semantic layers, metadata, metric definitions, documentation, and data quality
• Experience integrating AI tools into analytics engineering workflows to improve development speed, quality, and scalability
• Familiarity with Salesforce and supporting commercial business areas
• Ability to identify user needs and translate them into scalable data products
• Skilled in breaking down ambiguous problems into tangible steps leading to impactful solutions
• Effective communication of findings to both technical and non-technical audiences

• Develop dbt data models, dashboards, metrics, and automation processes for the revenue field team and revenue analysts
• Build and maintain critical reporting data models that power external merchant reporting
• Build the semantic, metadata, and context layers for AI systems to understand Revenue data, metrics, and business definitions
• Partner with Business Systems, engineering, and business stakeholders to translate requirements into durable, well-tested data products
• Contribute to best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows)
• Develop processes, governance, and foundations to scale analytics impact within Revenue

The job description is not a contractual document and does not have binding force. Data processing is subject to applicable laws and company policies regarding personal data rights and recruitment process.