Staff Analytics Engineer - Foundational Data

Airbnb is a global company that connects hosts and guests for unique stays and experiences. The Staff Analytics Engineer will lead efforts in building high-quality datasets and provide technical mentorship to enhance data strategy across the organization.

Responsibilities:

• Develop high quality data assets to satisfy a wide range of use-cases
• Develop frameworks and tools to scale insight generation to meet critical business and infrastructure requirements
• Collaborate and build strong partnerships with other data practitioners throughout Airbnb
• Influence the trajectory of data in decision making
• Improve trust in our data by championing for data quality across the stack
• Influence event logging instrumentation best practices and participate in architecture designs

Requirements:

• 9+ years of experience with a BS/Masters or 6+ years with a PhD
• Fluent in SQL and proficient in at least one data engineering language, such as Python or Scala
• Expertise using business intelligence and reporting tools like Superset and Tableau
• Expertise in large-scale distributed data processing frameworks like Presto or Spark
• Expertise in data modeling for data warehouses and/or metrics repositories
• Experience with an ETL framework like Airflow
• Clear and mature communication skills: ability to distill complex ideas for technical and non-technical stakeholders
• Ability to provide technical leadership and mentorship, guiding teams on best practices and contributing to the development of analytic engineering strategies
• Experience exploring and leveraging LLM AI's in every-day tasks (coding, documentation, etc…)
• Strong capability to forge trusted partnerships across working teams
• Scaling data tasks via automation
• Previous experience in large-scale cloud-based software engineering or system architecture
• Experience with AB experimentation
• Familiarity with AI/ML algorithms, including their dependencies on data, as well as their respective strengths and limitations
• Designing and/or leveraging high quality data visualization tools