About the company
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.
Responsibilities
- Lead the design, implementation, and testing of data systems, from architecture to production
- Build batch and real-time data systems that support business needs and critical products
- Ensure data systems' quality, performance, and stability through rigorous monitoring and quality assurance practices
- Design and optimize data models to efficiently meet business and product requirements
- Collaborate with cross-functional teams, including product managers, data scientists, and engineers, to develop scalable systems and drive data-driven decisions
- Maintain strong partnerships with backend, data science, and machine learning teams to ensure seamless integration of data systems
- Contribute to long-term data strategies and influence data engineering practices across the organization
- Mentor and guide team members, fostering best practices for data quality and governance
- Advance 3rd party data integrations, enhancing frameworks for data exchange, governance, and lineage
Requirements
- 9+ years of relevant experience with a Bachelor's/Master’s degree in CS/EE (or 6+ years with a PhD)
- Extensive experience in designing, building, and operating distributed data platforms (e.g., Spark, Kafka, Flink) at a large scale
- Proficiency in Java, Scala, or Python, along with strong skills in data processing and SQL querying
- Proven track record of designing and optimizing batch and real-time data pipelines
- Strong collaboration skills with the ability to work with product managers, data scientists, and engineers
- Advanced problem-solving and analytical skills, with a focus on data quality, governance, and system reliability
- Excellent written and verbal communication, with the ability to influence stakeholders and convey complex technical concepts
- Expertise in data modeling, warehousing, and working with relational and columnar databases (e.g., PostgreSQL, MySQL, Redshift, BigQuery)
- Experience with integrating machine learning models into data systems (preferred)
- Strong leadership and mentorship capabilities, with experience guiding teams on best practices and technical strategies
- Flexible and innovative, with the ability to adopt new technologies to enhance data systems and processes