Senior Staff Data Engineer, Foundational Data (Remote)

Airbnb; United States; Remote; USD 150,000 - 230,000; Full time

Job summary

United States Digital Space LLC is seeking a Senior Staff Data Engineer to own long-term data architecture and build Airflow pipelines ingesting telemetry, logs, and billing data, plus dimensional models used company-wide.

This hands-on role requires deep data engineering expertise, strong SQL and Python, and the ability to set direction for analytics engineering while collaborating across Infrastructure, Finance, and Product Engineering.

Qualifications

• 12+ years of relevant industry experience with a BS/MA, or 9+ years with a PhD, in data engineering or a closely related field.
• Production data pipelines at scale; strong SQL and Python.
• Ability to design a dimensional model and define a trusted metric.
• Experience as a technical lead shaping direction while coding.
• Ability to quickly grasp unfamiliar data domains and model them well.

Responsibilities

• Provide technical leadership across data engineering and analytics engineering for cost, traffic, and infrastructure intelligence.
• Define and own multi-year data strategy and architecture for foundational data assets.
• Own the measurement of AI unit economics, GPU fleet utilization, and developer AI tooling costs.
• Design and build datasets that integrate cost, utilization, performance, and reliability signals across fleets.
• Stay hands-on in pipelines and models to catch design-time issues.
• Influence and coach a distributed team of Data Engineers and Analytics Engineers.
• Navigate conflicting stakeholder requirements across Infrastructure, Finance, Data Science, and Product Engineering.
• Participate in on-call rotation for owned datasets.

Skills

SQL

Python

Dimensional modeling

Data pipelines

Leadership

Education

BS/MA in data engineering or related field

PhD (optional)

Tools

Airflow

Job description

United States Digital Space LLC is seeking a Senior Staff Data Engineer to own long-term data architecture and build Airflow pipelines ingesting telemetry, logs, and billing data, plus dimensional models used company-wide.

This hands-on role requires deep data engineering expertise, strong SQL and Python, and the ability to set direction for analytics engineering while collaborating across Infrastructure, Finance, and Product Engineering.