Senior Data Engineer, Airbnb for Real Estate

Airbnb was born in 2007 when two Hosts welcomed three guests to their San Francisco home, and has since grown to over 4 million Hosts who have welcomed more than 1 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:

Whenever anyone thinks of Airbnb, the first thing that comes to mind is vacation homes . However this is actually a small segment of residential housing, the majority of the market is apartment homes. The Airbnb for Real Estate team’s mission is making these apartment homes more accessible for hosting on Airbnb. We do this by working with and supporting the owners, operators, and residents of these apartment homes. We also support professional hosts who partner with real estate operators to offer host stays in otherwise unutilized space.

The Difference You Will Make:

On the Airbnb for Real Estate team, you can have a significant impact on a wide range of Airbnb products and users. Whether you are working on one of our big bets or helping improve an established area of the business, you will be on a small team designed to maximize your ability to deliver results. If you are motivated by how much visibility your work has, how much it impacts the company's bottom line, how many users see your work, or how it will impact your career growth, the Airbnb for Real Estate team is a great place to launch your Airbnb career.

We are a small, entrepreneurial group within Airbnb. We move fast, and are passionate about our customers. We value and promote the diversity of our workforce, our guests, our hosts, our marketplace platform, and the world. We are an equal opportunity employer: We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

A Typical Day: 

• Design, build, 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 merchandising optimization. Ensure data quality, consistency, and accuracy.
• Build scalable data pipelines (SparkSQL & Scala) leveraging …