Staff Data Engineer, Tech Foundations

Role and Team

Airbnb’s Enterprise Core Datasets team within Tech Foundations builds trustworthy data foundations for business decisions, product innovation, and operational efficiency. Its scope includes AI adoption, usage and cost; Unit Economics; enterprise application data; and financial metrics such as Gross Booking Value and Revenue.

As a Staff Data Engineer, you will provide hands-on technical leadership across problem definition, architecture, implementation, validation, and production operations. You will build extensible, reusable data foundations in an ecosystem containing petabyte-scale datasets and improve correctness, freshness, performance, and cost efficiency.

Responsibilities

• Lead architecture, implementation, and operation of pipelines covering AI usage and cost, Unit Economics, enterprise applications, and financial metrics.
• Partner with stakeholders to define consistent measures and data models for AI adoption, consumption, and spending.
• Connect revenue and cost drivers to support analysis of product profitability and resource efficiency.
• Build ingestion and transformation pipelines for Jira and other enterprise applications.
• Translate ambiguous requirements into source contracts, reusable fact and dimension models, and technical designs.
• Develop configurable pipelines and shared components to simplify onboarding new sources, products, and requirements.
• Establish automated testing, reconciliation, anomaly detection, and monitoring for data accuracy, completeness, and availability.
• Lead migrations and historical backfills using dependency analysis, validation, controlled cutovers, and recovery planning.
• Optimize distributed processing, storage, and queries to improve freshness and reduce compute costs.
• Own production reliability through on-call participation, incident response, and improvements to systems and runbooks.
• Shape the technical roadmap, lead design reviews, mentor engineers, and improve Airbnb’s Data Engineering Paved Path.

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; alternatively, 6+ years of relevant experience with a PhD.
• Track record of leading complex data engineering initiatives from ambiguous requirements through architecture, delivery, and sustained production ownership.
• Deep SQL expertise 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 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 incident recovery practices.
• Strong performance engineering skills across distributed computation, storage, and query execution.
• Ability to align engineering and business stakeholders, communicate architectural tradeoffs, and drive cross-team decisions.
• Demonstrated technical leadership through mentorship, architectural guidance, and improvements to shared engineering practices.
• Curiosity and sound judgment when learning new domains and balancing delivery needs with long-term system health.

Preferred Experience

• AI usage or cost measurement, cloud cost attribution, Unit Economics, enterprise application data, or financial and payments datasets.
• Familiarity with workflow orchestration, SQL transformation frameworks, and modern table formats such as Apache Iceberg.

Location

This position is US remote eligible and may include occasional office work or offsite attendance as agreed with the manager. Employees must live in a state where Airbnb, Inc. has a registered entity. State eligibility exclusions may change; candidates should check Airbnb’s current list. A recruiter will explain state eligibility if another Airbnb entity employs the role.

Recruitment and Accommodations

• Applicants needing disability-related recruitment accommodations should notify their recruiter once contacted.
• Official roles are posted at careers.airbnb.com. Recruiters use only @airbnb.com or @ext.airbnb.com email addresses.
• During interviews, Airbnb will not request Social Security numbers, bank details, passports, payment app information, fees, money transfers, check deposits or cashing, or purchases of work equipment.