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 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,