Databricks shows how their tech empowers Zillow’s developers via self-service ETL.
These tools abstract away the orchestration, deployment, and Apache Spark processing implementation from their respective users. In this talk, Zillow engineers discuss two internal platforms they created to address the specific needs of two distinct user groups: data analysts and data producers. Each platform addresses the use cases of its intended user, leverages internal services through its modular design, and empowers users to create their own ETL without having to worry about how the ETL is implemented.
Members of Zillow’s data engineering team discuss:
Why they created two separate user interfaces to meet the needs different user groups
What degree of abstraction from the orchestration, deployment, processing, and other ancillary tasks that chose for each user group
How they leveraged internal services and packages, including their Apache Spark package — Pipeler, to democratize the creation of high-quality, reliable pipelines within Zillow.