Staff Analytics Analyst, Full Stack (Revenue)

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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.<br><br><strong>About The Team<br><br></strong>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.<br><br><strong>About The Role<br><br></strong>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.<br><br><strong>What You’ll Do<br><br></strong><ul><li>Lead high-impact data product initiatives for Revenue, from ambiguous problem definition through technical design, implementation, rollout, and adoption. </li><li>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. </li><li>Design and build durable, well-tested data products that power revenue operations, field and executive reporting, external merchant reporting, and analyst self-service. </li><li>Set technical direction for Revenue’s data layer across dbt models, metrics, semantic structures, documentation, lineage, testing, governance, and access controls. </li><li>Identify opportunities to simplify, automate, and scale Revenue Analytics through improved data architecture, tooling, governance, and enablement. </li><li>Provide technical leadership and mentorship to analysts and cross-functional partners, raising the bar for how data products are designed, built, and maintained. <br><br></li></ul><strong>What We Look For<br><br></strong><ul><li>7+ years of experience in analytics engineering, business intelligence, data engineering, data product development, or a related technical analytics role. </li><li>Deep expertise in SQL, dbt, data modeling, metrics design, data quality, documentation, and modern analytics engineering practices. </li><li>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. </li><li>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. </li><li>Demonstrated ability to independently lead complex, ambiguous projects by defining scope, sequencing work, managing tradeoffs, aligning stakeholders, and delivering durable technical solutions. </li><li>Experience designing scalable data products for multiple audiences and influencing technical and non-technical stakeholders around architecture and product direction. </li><li>Familiarity with Salesforce and experience supporting commercial, GTM, revenue, or sales operations teams. <br><br></li></ul>Pay Grade - O<br><br>Equity Grade - 12<br><br>Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.<br><br>Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)<br><br>USA base pay range (CA, WA, NY, NJ, CT) per year: $220,000 - $280,000<br><br>USA base pay range (all other U.S. states) per year: $195,000 - $255,000<br><br>Please note that visa sponsorship is not available for this position.<br><br>Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities.<br><br><strong>Benefits<br><br></strong>We’re extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:<br><br><ul><li>Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents </li><li>Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses</li><li>Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge</li><li>ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount<br><br></li></ul>We believe It’s On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.<br><br>[For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records.<br><br>By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.<br><br>

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