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Salary: USD 212,000 - 265,000 / annual
Airbnb's Data Warehouse Infrastructure team is seeking a Staff Software Engineer to design and build the next generation of big data compute platforms that power data ETL, analytics, and machine learning across the company. You will work with open-source technologies including Hadoop, Spark, Trino, Iceberg, and Airflow to support hundreds of engineers managing and analyzing data at scale.
In this role, you will:
- Design and architect the next-generation big data compute platform to empower data ETL, analytics, and machine learning initiatives
- Operate, manage, and improve the reliability, performance, observability, and cost efficiency of the platform
- Write maintainable, self-documenting code and perform thorough code reviews
- Contribute to open-source software projects and drive industry impact
- Collaborate with cross-functional teams to define system requirements, identify solutions, and integrate systems
- Troubleshoot and resolve complex data infrastructure problems
This is a remote-eligible position within the US, with occasional office work or offsites as agreed with your manager. You must reside in a state where Airbnb, Inc. maintains a registered entity (check the careers page for excluded states).
Requirements:
- BS/MS/PhD in Computer Science or related field, or equivalent work experience
- 10+ years of experience working with data infrastructure, with focus on big data technologies
- Proficiency in big data technologies such as Spark, Presto/Trino, and Kubernetes
- Strong programming skills in Java and/or Scala
- Extensive experience designing, building, and maintaining scalable, fault-tolerant distributed systems
- Demonstrated expertise in multi-threading and concurrency programming
- Familiarity with both SQL and NoSQL database systems
- Proven ability to collaborate across teams and integrate complex systems
- Strong troubleshooting and problem-solving capabilities
- Excellent written and verbal communication skills
- Ability to work effectively in a team environment
