Airbnb was born in 2007 when two Hosts welcomed three guests to their San Francisco home, and has since grown to over 4 million Hosts who have welcomed more than 1 billion guest arrivals in almost every country across the globe. Every day, Hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.
Airbnb has become a global platform that connects travelers and hosts in approximately 100,000 cities around the world. Our mission is to enable a world where anyone can belong anywhere.
About the position:
Analytics Engineers build the data foundation for reporting, analysis, experimentation, and machine learning at Airbnb. 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, you will transform data from data warehouse tables into valuable data artifacts that power impactful analytic use cases (e.g. metrics, dashboards). 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.
Your Responsibilities:
- Understand data needs by interfacing with fellow Analytics Engineers, Data Scientists, Data Engineers, and Business Partners
- Architect, build, and launch efficient & reliable new data models and pipelines in partnership with Data Engineering
- Design, define, and implement metrics and dimensions to enable analysis and predictive modeling
- Become a data expert in your business domain and own data quality
- Build tools for auditing, error logging, and validating data tables
- Build and improve data tooling in partnership with internal Data Platform teams
- Define logging needs in partnership with Data Engineering
- Design and develop dashboards to enable self-serve data consumption
Required Qualifications:
- Passion for building high quality assets and scaling data
- 4+ years of relevant industry experience
- Strong skills in SQL and distributed system optimization (e.g. Spark, Presto, Hive)
- Expert in at least one programming language for data analysis (e.g. Python, R)
- Experience in schema design and dimensional data modeling
- Ability to perform basic statistical analysis to inform business decisions
- 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