Senior Software Engineer, Data Engineering
AirbnbUnited StatesPosted 18 March 2026
Job Description
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.
The Community You Will Join:
We are currently hiring for multiple teams:
Guest Data: Understanding how guests and hosts use Airbnb allows us to give them the best possible experience. The Guest Data team, part of the Guest Host organization, is dedicated to developing top-tier tools, frameworks, and data models that offer a data-driven perspective on guest experiences on Airbnb products. Our primary stakeholders include analytics and data science partners, ML engineers, and product and engineering leaders involved in the core booking flow.
Airbnb is powered by our Host and Guest communities. Our teams work on everything from driving improvements for the end-to-end Host and Guest experience to launching new product verticals from the ground up. Our job is to build world-class, comprehensive platforms and features to create high-quality experiences for our outstanding community of Hosts and Guests. Listings and Host Tools Data and AI (LHT-DnA) team is one of the 4 teams of the Marketplace-DnA org: The LHT-DnA team supports host personalization products and provides data driven solutions to achieve superior host experience on Airbnb. These products include but are not limited to managing your space (MYS), host quality standards etc. We own data pipelines and ML models and will build services for serving that are used in the above areas.
Data Foundation: Our mission in the Foundational Data team is to build and maintain high quality datasets frequently used across all of Airbnb. We set company-wide standards that decide how locations are grouped into regions, visitors are measured based upon site traffic, bot traffic is separated from organic traffic, and cloud costs are attributed to Airbnb services. This data is used to build public financial reports, drive strategic marketing decisions, and manage operational costs. By collaborating with cross-functional teams, you will have the opportunity to drive significant business impact.
The Difference You Will Make:
Guest Data: As a Senior Data Engineer, you will help build our data strategy, develop top-tier data models and tooling, and provide technical leadership to a team of senior data engineers. You have the opportunity to influence critical aspects of the Airbnb experience, including Search and Checkout, while collaborating with long-standing xfn partners across Product, Analytics Engineering, Data Science, Infrastructure, and AI/ML. Your work will impact the quality of the Airbnb product experience for millions of daily visitors, making it an exciting opportunity for anyone passionate about data and its transformative potential.
Data Foundation:
You will bring a unique lens to our data strategy and provide in-depth technical mentorship and leadership to the team. We are looking for someone with experience that spans a wide range of skills centered around data. You will be responsible for developing data models that balance competing requirements, interacting with technical non-technical data users, managing large-scale data projects, and maintaining data pipelines. Staff-level engineers are expected to do this with a minimal amount of supervision. We value innovative thinkers who consistently seek smarter and more efficient solutions while managing daily operations, deadlines, and collaborating with team members.
A Typical Day:
Design, bui ld, and maintain robust and efficient data pipelines that collect, process, and store data from various sources, including user interactions, listing details, and external data feeds.
Develop data models that enable the efficient analysis and manipulation of data for mer ... (truncated, view full listing at source)
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