Analyst II, Full Stack (Revenue Analytics)

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. We’re looking for a curious, driven professional to join our Revenue Analytics team. This builds and owns the data products, reporting infrastructure, semantic foundations, and analytical systems that power Affirm’s Revenue organization. As a Senior Analyst, Revenue Analytics, you’ll build scalable data products that power day-to-day decision-making - owning end-to-end work across data modeling, metric definitions, dashboards, automation, and enablement. You’ll also help strengthen our semantic layer and data governance, laying the foundation for reliable AI. The ideal candidate combines strong technical and analytical skills with the ability to turn ambiguous business questions into durable, well-tested data infrastructure. What you'll do - 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 that allow AI systems to accurately 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 the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows) - Develop processes, governance, and foundations to scale the impact of analytics within Revenue. • What we look for - 3+ years of work experience in an analytics engineering or business intelligence role - Strong working knowledge of SQL, dbt, Python, data modeling, and data visualization - Hands-on experience with BI tools (Sigma/Looker/Tableau), Databricks, and cloud data warehouses (Snowflake) - Understanding of the data foundations required for reliable AI, including semantic layers, metadata, evals, metric definitions, documentation, and data quality - Demonstrated experience integrating AI tools into day-to-day analytics engineering workflows to improve development speed, quality, and scalability - Familiarity with Salesforce and experience supporting commercial areas of the business - Ability to identify user needs and translate them into robust, scalable data products - Ability to start with an ambiguous problem, deconstruct it into tangible steps, and work toward an impactful solution - Ability to communicate findings and recommendations clearly to both technical and non-technical audiences. Compensation and Benefits Base Pay Grade - K Equity Grade - Poland 2 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. Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company). POL base pay range per year: 226 000 zł - 346 000 zł Additional benefits include: - Type of employment: Contract of Employment - Flexible Spending Wallets for tech, food and lifestyle - Away Days - wellness days to take off work and recharge - Learning & Development programs - Parental benefits - Employee Resource & Community Groups This role is eligible for creative tax benefits, subject to applicable law and company policy Location - Remote Poland The majority of our roles can be located anywhere in Poland. **This job description is not a contractual document, and is not intended to have binding force.** #LI-Remote 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. 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: - Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents - Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses - Time off - competitive vacation and holiday sc

3+ years of experience in analytics engineering or business intelligence. Strong working knowledge of SQL, dbt, Python, data modeling, and data visualization. Hands-on experience with BI tools (Sigma/Looker/Tableau), Databricks, and cloud data warehouses (Snowflake). Understanding of the data foundations required for reliable AI, including semantic layers, metadata, evals, metric definitions, documentation, and data quality. Demonstrated experience integrating AI tools into day-to-day analytics engineering workflows to improve development speed, quality, and scalability. Familiarity with Salesforce and experience supporting commercial areas of the business. Ability to identify user needs and translate them into robust, scalable data products. Ability to start with an ambiguous problem, deconstruct it into tangible steps, and work toward an impactful solution. Ability to communicate findings and recommendations clearly 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 that allow AI systems to accurately 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 the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows). Develop processes, governance, and foundations to scale the impact of analytics within Revenue.