Case Study: Bread Pay achieves 90% faster data processing and scalable payments analytics with Databricks

Secure and personalized payment options for customers at scale

Bread, a technology-driven payments division of Alliance Data Systems, provides personalized financing for merchants and over 1 million customers. As data volumes grew from gigabytes to terabytes, their Snowflake-based CSV ingestion pipeline became a bottleneck—daily dumps and hour‑plus jobs (90 minutes) couldn’t support near‑real‑time analytics, and siloed sources and toolchains created dependencies between data engineering, analytics, and data science.

Bread migrated to the Databricks Lakehouse on AWS, using Delta Lake, Autoloader, Spark jobs, Delta Live Tables and the Databricks SQL Connector to unify ingestion, ETL and analytics. The change cut processing time from 90 minutes to 10 (90% faster), enabled handling 140× more data for only 1.5× the cost, and increased actionable insights for reporting by 20%, while supporting fraud detection, credit risk, recommendations and broader data democratization.

Bread Pay

Christina Taylor

Staff Data Engineer