Senior Staff Data Engineer, Foundational Data
New
A
AirbnbCloud Infrastructure
Position is completely Remote- USA. While the position is Remote Eligible, you must live in a state where Airbnb Payments, Inc. (a subsidiary of Airbnb, Inc.) is a registered entity.Full-TimeSenior
Salary$248,000 — $310,000 USD
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Job Details
- Experience
- 12+ years of relevant industry experience with a BS/Masters, or 9+ years with a PhD
- Required Skills
- PythonSQLAirflowData engineering
Requirements
- 12+ years of relevant industry experience with a BS/Masters, or 9+ years with a PhD, in data engineering or a closely related field
- Designed, built, and operated production data pipelines at large scale
- Strong SQL and Python proficiency
- Proven ability to design a dimensional model and define a metric others will trust
- Experience successfully moving into an unfamiliar data or technical domain and becoming productive quickly
- Demonstrated experience as a technical lead on a team or program, setting direction without formal authority
- Experience writing multi-year technical strategies that secured funding and execution
- Proven ability to build a data product from a blank page where no schema or precedent existed
- Strong documentation skills to align teams on contested technical decisions
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
- Stay hands-on in the pipelines and models you architect, close enough to the build to catch the 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
- Navigate conflicting stakeholder requirements across Infrastructure, Finance, Data Science, and Product Engineering
- Identify and eliminate duplication and data fragmentation across the engineering organization
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