Data Engineer

Expertise:

·       5-9+ years of relevant industry experience with a BS/Masters, or 2+ years with a PhD

·       Experience with distributed processing technologies and frameworks, such as Hadoop, Spark, Kafka, and distributed storage systems (e.g., HDFS, S3)

·       Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions

·       Expertise with ETL schedulers such as Apache Airflow, Luigi, Oozie, AWS Glue or similar frameworks

·       Solid understanding of data warehousing concepts and hands-on experience with relational databases (e.g., PostgreSQL, MySQL) and columnar databases (e.g., Redshift, BigQuery, HBase, ClickHouse)

·       Excellent written and verbal communication skills

A Typical Day:

·       Design, build, and maintain robust and efficient data pipelines that collect, process, and store data from various sources, including user interactions, financial details, and external data feeds.

·       Develop data models that enable the efficient analysis and manipulation of data for merchandising optimization. Ensure data quality, consistency, and accuracy.

·       Build scalable data pipelines (SparkSQL & Scala) leveraging Airflow scheduler/executor framework

·       Collaborate with cross-functional teams, including Data Scientists, Product Managers, and Software Engineers, to define data requirements, and deliver data solutions that drive merchandising and sales improvements.

·       Contribute to the broader Data Engineering community at Airbnb to influence tooling and standards to improve culture and productivity

·       Improve code and data quality by leveraging and contributing to internal tools to automatically detect and mitigate issues.

·       Skill Sets - Python, SQL (expert level), Spark and Scala (intermediate).