Senior Staff Data Engineer, Foundational Data

About the role

Airbnb was founded in 2007 and now has over 5 million hosts and over 2 billion guest arrivals worldwide. The Foundational Data team builds high‑quality datasets that power decisions on site traffic, bot separation, cloud cost attribution, and AI model cost, usage, and performance. As a Senior Staff Data Engineer you will be the technical leader for this mixed Data Engineering/Analytics Engineering team, setting the long‑term data architecture, building pipelines and dimensional models, and influencing how Airbnb measures its AI investments. The position is remote‑eligible within the United States; you must reside in a state where Airbnb Payments, Inc. is a registered entity (currently Alabama, California, Florida, Georgia, Illinois, Minnesota, Mississippi, Nevada, New Jersey, New York, North Carolina, Ohio, Oregon, Pennsylvania, Tennessee, Texas, or Washington).

Responsibilities

• Provide technical leadership across the team's data engineering and analytics engineering work, spanning cloud cost, traffic & bots, and infrastructure intelligence
• Define and own the multi‑year data strategy and architecture for Airbnb's foundational data assets, and build the cross‑org consensus needed to fund and execute it
• Own how Airbnb measures its AI: the unit economics of training and serving our own models, GPU fleet utilization, and the cost and adoption of developer AI tooling
• Design and build the datasets that integrate cost, utilization, performance, and reliability signals across Airbnb's infrastructure fleets, starting from a blank page
• Stay hands‑on in the pipelines and models you architect, close enough to the build to catch problems design reviews miss
• Influence and coach a distributed team of Data Engineers and Analytics Engineers, raising the quality bar through design and code review and scaling it by building frameworks and automated checks other teams adopt
• Navigate conflicting stakeholder requirements across Infrastructure, Finance, Data Science, and Product Engineering, and land