Airbnb is hiring a
Staff Data Engineer

Summary

Join Airbnb's data engineering team to build trustworthy data systems and drive business innovation. As a senior data engineer, you'll partner with cross-functional teams to design and productionize batch and real-time data pipelines, ensuring quality, performance, and stability. You'll work on critical Tier-1 company-wide metrics, such as Gross Booking Value and Revenue, and contribute to the development of long-term data strategies.

Requirements

• 9+ years of relevant industry experience with a Bachelor’s and/or Master’s degree in CS/EE, or equivalent experience, or 6+ years of experience with a PhD
• Extensive experience designing, building, and operating robust distributed data platforms (e.g., Spark, Kafka, Flink, HBase) and handling data at the petabyte scale
• Strong knowledge of Java, Scala, or Python, and expertise with data processing technologies and query authoring (SQL)
• Proven ability to design, productionize, and optimize batch and real-time data pipelines and systems, ensuring their quality, performance, and stability
• Excellent ability to collaborate with cross-functional teams, including product managers, engineers, data scientists, and business partners, to align on requirements and drive data-driven decision-making
• Advanced analytical and problem-solving skills with a focus on data quality, governance, and system reliability
• Exceptional written and verbal communication skills, capable of influencing stakeholders and conveying complex technical concepts effectively
• Expertise in data modeling, warehousing, and working with relational (e.g., PostgreSQL, MySQL) and columnar databases (e.g., Redshift, BigQuery)

Responsibilities

• Architect and productionize batch and real-time data systems to support various products and business needs
• Ensure the quality, performance, and stability of data systems through robust quality systems and monitoring practices
• Design and optimize data models for efficient storage and retrieval to meet critical product and business requirements
• Collaborate with cross-functional teams, including product managers, engineers, data scientists, and business partners, to align on data requirements and develop scalable systems
• Tune, productionize, and optimize data systems and machine learning models to enhance their effectiveness and efficiency
• Build and maintain strong relationships with partner engineering teams, including backend, client, data science, and ML teams, to ensure seamless integration and support
• Contribute to the development of long-term data strategies and roadmaps, and influence the technical direction of data engineering practices within the organization
• Mentor and coach team members, providing guidance and support to enhance their skills and performance

Benefits

• Bonus
• Equity
• Benefits
• Employee Travel Credits