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 are in search of an action-oriented and analytically inclined Analytics Engineer to join the People Analytics organization and significantly expand our data integration, transformation, and reporting capabilities. People Analytics is responsible for the infrastructure, business logic, and deliverables for data across the People space; including talent acquisition, total rewards, feedback & development, and employee data. This position will be instrumental in architecting and building robust data infrastructure and tools, significantly enhancing our team’s ability to deliver high-value data products across the business.
This role is primarily suited for candidates with strong data skills, particularly with experience in the design and creation of ETLs and SQL-based relational database structures. The ideal candidate will not only have superb technical skills but also strong interpersonal skills and the ability to take a leading role in driving our data and reporting capabilities to the next level. You’ll have the opportunity to make a significant impact by building robust data infrastructure and tools that empower our People Analytics organization and cross-functional partners across the business. Join our team and be part of Affirm’s mission to reinvent credit!

• Design and deliver relational and non-relational database models, data pipelines, reporting and visualization solutions by supporting all phases of the analytics development life cycle (ADLC), including requirements gathering, design, development, testing and deployment
• Develop and maintain robust ETL/ELT pipelines for various HR data sources (e.g., Workday, Greenhouse Recruiting)
• Architect and implement scalable data models optimized for performance and analytical querying
• Ensure data quality, integrity, and reliability across all data assets
• Collaborate with People Analytics team members to understand data requirements and translate them into technical solutions
• Manage and optimize cloud data warehouse infrastructure (e.g., Snowflake)
• Leverage AI and LLMs to, for example, automate data quality checks, enhance metadata management, and extract deeper insights from unstructured HR data
• Be on the lookout for technology best practices and advocate for them
• Be an advocate for data governance, security, privacy, quality and retention