Staff Data Engineer, Tech Foundations

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. Staff Data Engineer, Enterprise Core Datasets, Tech Foundations The Community You Will Join: At Airbnb, trustworthy data powers business decisions, product innovation, and operational efficiency. The Enterprise Core Datasets team builds the technical data foundations that help Airbnb understand how the business operates, where resources are invested, and how new technologies create value. Our scope spans high-impact datasets across the organization: measuring AI adoption, usage, and cost; understanding revenue, costs, and profitability through Unit Economics; integrating non-platform data from Jira and other enterprise applications; and powering critical company metrics such as Gross Booking Value and Revenue. You will join a team that values thoughtful architecture, engineering rigor, and operational ownership. We collaborate with engineering, product, analytics, finance, and business teams to turn complex requirements into dependable, reusable data assets. We welcome strong engineers who are curious about the business and eager to solve problems across diverse domains. The Difference You Will Make: As a Staff Data Engineer, you will provide hands-on technical leadership for datasets that shape decisions across Airbnb. Your work will help the organization measure AI adoption and spending, understand the economics of its products, and connect enterprise application data to meaningful business and operational insights. You will lead complex initiatives from problem definition and architectural design through implementation, validation, and production operations. You will build extensible data foundations that accommodate new AI tools, products, cost categories, and enterprise systems while maintaining clear definitions, traceability, and reliable historical data. Operating in an ecosystem that includes petabyte-scale datasets, you will improve correctness, freshness, performance, and cost efficiency. You will develop reusable frameworks that simplify source onboarding, reduce duplicated logic, and make critical data easier to discover and use. Through mentorship and contributions to Airbnb’s shared data engineering tools and standards, your impact will extend across the data community. A Typical Day: Lead the architecture, implementation, and operation of high-impact data pipelines across AI usage and cost, Unit Economics, enterprise applications, and critical Financial metrics. Partner with stakeholders to define how AI adoption, consumption, and spending are measured across the organization, and build consistent data models that support those definitions. Evolve Unit Economics datasets to connect revenue and diverse cost drivers, enabling teams to understand product profitability and resource efficiency. Build reliable ingestion and transformation pipelines for non-platform systems such as Jira and other BizTech enterprise applications. Translate ambiguous requirements into clear source contracts, reusable fact and dimension models, and technical designs. Develop configurable pipelines and shared components that simplify onboarding new data sources, products, and business requirements. Establish automated testing, reconciliation, anomaly detection, and monitoring to protect data accuracy, completeness, and availability. Lead safe migrations and historical backfills through dependency analysis, validation, controlled cutovers, and recovery planning. Optimize distributed processing, storage, and query performance to improve freshness and reduce compute costs. Own production reliability through on-call participation, incident response, and lasting improvements to systems and runbooks. Shape the technical roadmap, lead design reviews, mentor engineers, and contribute improvements to Airbnb’s Data Engineering Paved Path. Your Expertise: 9+ years of relevant industry experience with a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience; or 6+ years of relevant experience with a PhD. A track record of leading complex data engineering initiatives from ambiguous requirements through architecture, delivery, and sustained production ownership. Deep expertise in SQL and strong programming skills in Python or Scala, with experience building maintainable, well-tested data systems. Extensive experience with distributed processing technologies such as Apache Spark and large-scale analytical storage systems. Strong data modeling skills, including fact and dimension design, slowly changing dimensions, incremental processing, and historical data management. Experience integrating heterogeneous