About the job
Founded in 2007 when two hosts welcomed three guests into their San Francisco home, Airbnb has evolved into a global community of over 5 million hosts, facilitating more than 2 billion guest arrivals across nearly every country. Our hosts provide unique stays and experiences, allowing guests to forge authentic connections with diverse communities.
Join Our Community:
At Airbnb, our Foundational Data team is dedicated to creating and maintaining high-quality datasets that serve as the backbone for various operations across the organization. We establish company-wide standards that define how locations are categorized, how visitor traffic is analyzed, and how cloud costs are allocated. This critical data informs public financial reports, shapes strategic marketing initiatives, and helps manage operational expenses. By working collaboratively with cross-functional teams, you will be positioned to drive substantial business outcomes.
Your Impact:
As a Senior Staff Analytics Engineer, you will play a pivotal role in shaping our data strategy while providing advanced technical mentorship and leadership to your peers. We seek an individual with a strong background in data modeling, metric development, and experience with large-scale distributed data processing frameworks such as Presto or Spark. Utilizing our state-of-the-art data tools, you will empower both technical and non-technical teams to leverage data-driven insights for informed decision-making. Staff engineers are expected to operate with a high degree of autonomy, and we value innovative thinkers who are committed to finding smarter, more efficient solutions while effectively managing daily operations and meeting deadlines.
Daily Responsibilities:
- Create high-quality data assets that address a diverse range of business needs.
- Develop frameworks and tools that enhance insight generation to meet essential business and infrastructure demands.
- Build and nurture strong partnerships with fellow data professionals throughout Airbnb.
- Influence data-driven decision-making processes.
- Enhance trust in our data by advocating for quality across the data lifecycle.
- Contribute to best practices for event logging instrumentation and participate in architectural designs.

