Senior Staff Data Engineer, Marketplaces DNA

Details

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

Marketplaces Data and AI is a group of passionate machine learning, software, data, and analytics engineers. We are responsible for developing new, cutting-edge AI and data products that leverage Airbnb’s massive datasets across Users, Listings, Pricing, and Supply/Demand. You will be a crucial part of the Guest and Host organization, building the intelligence that powers the web and native apps used by hundreds of millions of guests and hosts globally.

Role summary

You will own some of the most critical data at Airbnb including Users, Listings, and Marketplaces. You will help uplevel data engineering practice and foundation while partnering with partner and infrastructure teams to ship data products and ML models. This is a unique opportunity to shape how we develop data products for the Users, Listings, and Marketplaces teams and across Airbnb.

Responsibilities

• Develop and automate large-scale, high-performance batch and streaming data processing systems to power Airbnb’s Guest and Host products, machine learning models, and business insights.
• Understand business and product needs and align with software engineers, ML engineers, and data scientists on data flow and foundational data models.
• Build scalable data architectures focused on latency and volume, operating at petabyte scale.
• Partner closely with infrastructure teams to improve scalability, data governance, and efficiency.
• Evangelize high-quality software engineering practices for building data infrastructure and pipelines at scale.
• Advocate for high data and engineering quality: ensure deliverables are reliable, efficient, well documented, testable, and maintainable.
• Design data models and thoughtful dataflows to power critical product and business requirements.

Requirements / Your expertise

• 12+ years of relevant industry experience with a Bachelor’s and/or Master’s degree in CS/EE, or equivalent experience; or 9+ years with a PhD.
• Experience collaborating with client, backend, ML, and analytics teams, product and business partners.
• Experience designing and deploying high-performance systems with reliable monitoring and logging practices.
• Strong ability to work across team boundaries to establish overarching data architecture and data flow, and provide guidance to individual teams.
• Strong knowledge of relational databases and query authoring (SQL).
• Strong expertise with Java / Scala / Spark and operating on data at the petabyte scale.
• Experience building and operating both batch and streaming data pipelines.
• Excellent written and verbal communication skills.

Location & working model

• This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed with your manager.
• You must live in a state where Airbnb, Inc. has a registered entity (some states are excluded; check Airbnb careers for details).

Inclusion & accommodations

Airbnb is committed to working with the broadest talent pool possible. Diverse ideas foster innovation and engagement. All qualified individuals are encouraged to apply.

We provide a disability-inclusive application and interview process. Candidates requiring reasonable accommodation should contact [email protected] with their full name, the role, and the accommodation needed.

Compensation & benefits

• Base pay range: $244,000—$305,000 USD. The actual base pay depends on factors such as experience, skills, business needs and market demands. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Other notes

• Titles may span more than one career level; the actual level and compensation will depend on background and experience.