Airbnb Senior Staff Engineer App Foundation 

United States 

810146819

The Difference You Will Make:

Things you will do:

• Drive the development of batch and streaming data processing systems
• Work at the intersection of online and offline data, storage layers, and stream processing to create innovative solutions.
• Contribute to and work with open-source software, making an impact on the industry.
• Lead the execution of our next-generation architecture redesign initiatives.
• Evangelize high-quality software engineering practices towards building data infrastructure and pipelines at scale.

A Typical Day:

• Work with partners across orgs (client, backend, ML, and analytics teams) to design and deliver high-quality systems.
• Create paved paths and best practices for data processing systems and drive alignment and adoption across the company
• Lead efforts to architect, prototype, build and launch solutions for serving data pipelines that power product engineers across Airbnb to be productive and create delightful user experiences.
• Provide critical input in team roadmap and technical direction.
• Influence and collaborate with stakeholders to adopt team goals and roadmaps.
• Build efficient and backend solutions that are reliable, performant and scalable.
• Mentor engineers both within and outside the team.

Your Expertise:

• 12+ years of full-time work experience in software engineering and distributed systems.
• Strong expertise in batch & real-time data processing technologies like Flink, Spark, and building high-performance, data-intensive systems.
• Hands-on experience with Kafka and building services for Kafka at scale.
• Proficiency in designing and implementing GraphQL-based APIs.
• Strong knowledge of relational databases, SQL, and experience with Elasticsearch.
• Experience with Java / Scala / Spark and operating on data at the petabyte scale.
• Demonstrated ability to work effectively across team boundaries and provide guidance to individual teams.
• Excellent communication skills, both written and verbal, with a track record of collaborating with product managers, data scientists, and other engineering leaders and teams.