Data Engineer, Global Markets
Description For Data Engineer, Global Markets
Airbnb, founded in 2007, has grown from hosting three guests in San Francisco to facilitating over 1 billion guest arrivals globally. The Global Markets engineering team is seeking a Data Engineer to drive international growth through data-driven innovation. As a Data Engineer, you'll be crucial in bridging the gap between data producers and consumers, ensuring trustworthy data for innovation and operations across 220+ countries and regions.
You'll work on designing and maintaining robust data pipelines, processing data from various sources including user interactions and listing details. Using technologies like SparkSQL, Scala, and Airflow, you'll build scalable solutions while ensuring data quality and system stability. You'll collaborate with Data Scientists, Product Managers, and Software Engineers to deliver impactful data solutions.
The role requires expertise in distributed processing technologies (Hadoop, Spark, Kafka), strong analytical skills, and experience with ETL schedulers. You'll be part of a team focused on evolving guest and host experiences in global markets, making Airbnb feel like home for users worldwide. This remote position offers the opportunity to work with diverse teams and contribute to Airbnb's mission of creating authentic community connections through unique stays and experiences.
Responsibilities For Data Engineer, Global Markets
- Design, build, and maintain robust and efficient data pipelines
- Build scalable data pipelines using SparkSQL & Scala leveraging Airflow scheduler/executor framework
- Ensure the quality, performance, and stability of data systems
- Collaborate with cross-functional teams to define data requirements and deliver solutions
- Improve code and data quality through internal tools
- Work across multiple repositories, services, and environments
Requirements For Data Engineer, Global Markets
- 3+ years of relevant industry experience
- Experience with distributed processing technologies (Hadoop, Spark, Kafka, HDFS, S3)
- Ability to analyze large data sets
- Expertise with ETL schedulers (Apache Airflow, Luigi, Oozie, AWS Glue)
- Expert in at least one programming language for data analysis (Python, R)
- Excellent written and verbal communication skills
