Case Study: easyJet Holidays achieves 15x faster data pipelines with Dagster Labs

easyJet holidays speeds data pipelines 15x with Dagster Labs

easyJet holidays, the package holiday division of the easyJet airline, faced significant challenges with its fragmented AWS data stack. Their inefficient system, which used Airflow, Glue, and Redshift, lacked a unified control plane for observability, suffered from poor reliability requiring manual intervention, and created collaboration silos between data engineers and analysts. This led to long pipeline runtimes and dedicated support resources for troubleshooting.

By implementing Dagster Labs' data orchestration platform, easyJet holidays rebuilt its data platform with a modern, code-first architecture. The solution provided end-to-end visibility, enabled self-healing pipelines, and democratized analytics by allowing analysts to contribute via pull requests. The results were dramatic: Dagster Labs helped achieve a 15x faster pipeline execution time, reducing it from 2.5 hours to 10 minutes, which eliminated the need for dedicated support resources and significantly improved data freshness.

easyJet holidays