Senior Data Scientist - Analytics Engineering, Central Data

Airbnb is a mission-driven company dedicated to helping create a world where anyone can belong anywhere. It takes a unified team committed to our core values to achieve this goal. Airbnb's various functions embody the company's innovative spirit and our fast-moving team is committed to leading as a 21st century company.

About the Team

The Airbnb Central Analytics Engineering team is looking for a Senior Analytics Engineer to join our team. We own and curate central data models, data resources, and metrics that are critical to our business. In this role you will own some of Airbnb’s most foundational data assets, including our visitor, traffic, and location data.

About the Position

Analytics Engineers build the data foundation for reporting, analysis, experimentation, and machine learning. We are looking for someone with expertise in metric development, data modeling, SQL, Python, and large-scale distributed data processing frameworks like Presto or Spark. Using these tools, along with first-class internal data tooling, you will transform data from data warehouse tables into critical data artifacts that power impactful analytic use cases (e.g. metrics, dashboards) and empower downstream data consumers. As a Data Scientist on the Analytics Engineering track you will sit at the intersection of data science and data engineering, and work collaboratively to achieve highly impactful outcomes.

Data can transform how a company operates; high data quality and tooling is the biggest lever to achieving that transformation. You will make that happen.

Responsibilities:

• Understand data needs by interfacing with fellow Analytics Engineers, Data Scientists, Data Engineers, and Business Partners
• Architect, build, and launch efficient & reliable data models and pipelines in partnership with Data Engineering
• Design and implement metrics and dimensions to enable analysis and predictive modeling
• Design and develop dashboards or other data resources to enable self-serve data consumption
• Build tools for auditing, error logging, and validating data tables
• Define logging needs in partnership with Data Engineering
• Define and share best practices on metric, dimension, and data model development for analytics use
• Build and improve data tooling in partnership with Data Platform teams

Minimum Qualifications:

• Passion for high data quality and scaling data science work
• 6+ years of relevant industry experience
• Strong skills in SQL and distributed system optimization (e.g. Spark, Presto, Hive)
• Experience in schema design and dimensional data modeling
• Experience in at least one programming language for data analysis (e.g. Python, R)
• Proven ability to succeed in both collaborative and independent work environments
• Detail-oriented and excited to learn new skills and tools

Preferred Qualifications:

• Experience with an ETL framework like Airflow
• Python, Scala, Superset, and Tableau skills preferred
• An eye for design when it comes to dashboards and visualization tools
• Familiarity with experimentation and machine learning techniques