Senior Data Engineer, People Analytics

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.

The Community you will join:

People Analytics & Research is a strong team of Data Scientists, Researchers, and Analysts. Our work is highly sought-after, and we prioritize work that impacts employees and the business. If you have a background in Data Engineering and are excited to help build Airbnb’s community, we want to hear from you.

The difference you will make:

The People Analytics & Research team is looking for an experienced Data Engineer to support our growing portfolio of data  initiatives — from building data pipelines to  delivering data foundations and analytical products that power EX's growing suite of AI-driven tools. Your responsibility spans data infrastructure, analytics engineering, and data product development. The role is highly cross-functional,and you will work with Talent Leaders, Recruiting, Legal, Diversity and Belonging, and other core people-oriented teams, as well as contribute to the AI-driven tools that make people data more accessible across the organization.

Your Responsibilities:

• Collaborate with other team members and stakeholders to help understand data- and people-related business problems and translate them into scalable data solutions
• Build data pipelines and tables from HR systems such as Workday, Greenhouse, and other data sources
• Support Data Science team members in leveraging data for reporting, dashboard development, and other client-facing use-cases
• Build, update, and maintain a production-grade data foundation that supports AI initiatives — including pipelines that feed LLM-powered tools, evaluation and feedback datasets, and the access controls and data models required to responsibly scale AI products from prototype to production
• Design and deliver data products, including dashboards and reporting tools (e.g., Streamlit visualization apps), that surface actionable insights for non-technical stakeholders
• Write and optimize queries across both distributed query engine (Trino/Presto) and private relational database (Postgres)
• Align on priorities and work from a roadmap, ensuring you are focusing on the highest-priority projects
• Assess data readiness for AI use cases, working with EX teams, Legal, and BizTech to ensure sensitive employee data is handled with appropriate governance, permissioning, and access controls
• Support the transition of AI prototypes to production by building the underlying infrastructure — automated pipelines, security controls, and stable data models — that prototypes require to scale
• Exercise traits of adaptabi