The Challenge

A global sandwich and coffee chain with over £400 million in annual revenue and more than 6,000 employees faced growing inefficiencies in their data operations. Following a migration to Snowflake from a legacy Databricks environment, their data pipelines were carried over without optimisation resulting in suboptimal performance, unnecessary complexity, and underutilisation of Snowflake’s core capabilities.

Our Solution

To unlock greater value from their cloud investment, we rebuilt their data pipelines from the raw to base layers using streamlined, efficient processing techniques. The base schema was redesigned to better accommodate slowly changing dimensions, ensuring the platform could scale alongside the business’s evolving data needs while maintaining clarity, accuracy, and audibility.

The Impact

These improvements led to a 20% reduction in pipeline run time, directly lowering Snowflake credit consumption and operational costs. Additionally, enhanced data modelling and pipeline efficiency reduced the storage layer footprint by 40%, freeing up resources and improving overall data manageability. With a modernised data foundation, the company is now better positioned to drive analytics, reporting, and innovation with confidence and control.