[Hiring] Staff Data Engineer @Airbnb

Role Description

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.

• Lead complex initiatives from problem definition and architectural design through implementation, validation, and production operations.
• Build extensible data foundations that accommodate new AI tools, products, cost categories, and enterprise systems while maintaining clear definitions, traceability, and reliable historical data.
• Improve correctness, freshness, performance, and cost efficiency in an ecosystem that includes petabyte-scale datasets.
• Develop reusable frameworks that simplify source onboarding, reduce duplicated logic, and make critical data easier to discover and use.
• Mentor and contribute to Airbnb’s shared data engineering tools and standards, extending your impact across the data community.

Qualifications

• 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 sources, including APIs, enterprise applications, event data, and transactional systems, while managing schema changes and source reliability.
• Proven ability to build reliable pipelines and execute migrations and backfills while preserving correctness and downstream compatibility.
• Experience establishing data quality controls, observability, lineage, governance, and effective incident recovery practices.
• Strong performance engineering skills, including diagnosing bottlenecks and optimizing distributed computation, storage, and query execution.
• The ability to align stakeholders across engineering and business functions, communicate architectural tradeoffs, and drive decisions across team boundaries.
• Demonstrated technical leadership through mentorship, architectural guidance, and improvements to shared engineering practices.
• Curiosity and sound judgment when learning new domains and balancing immediate delivery needs with long-term system health.
• Experience with AI usage or cost measurement, cloud cost attribution, Unit Economics, enterprise application data, or financial and payments datasets is a plus.
• Familiarity with workflow orchestration, SQL transformation frameworks, and modern table formats such as Apache Iceberg is also valuable.

Requirements

• 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.

Benefits

• Remote eligible position with occasional work at an Airbnb office or attendance at offsites.
• Commitment to providing reasonable accommodations throughout the recruitment process for applicants with disabilities.

Company Description

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.