Case Study: SpotOn accelerates data insights by 6x with dbt Cloud
Key results
The challenge
As SpotOn scaled, its Postgres database was routinely slow, causing delayed ETL jobs and degraded BI reporting, and new analytics use cases were impossible to build. Engineering workflows centered on custom Python jobs in Airflow that required advanced skills, so only two engineers could consistently contribute and adding data sources took months. The data stack had become a bottleneck to the company's growth.
The solution
SpotOn migrated from Postgres to Snowflake and adopted dbt Cloud to manage transformations, alongside Metaplane for data observability. With core business logic in dbt, financial, operational, sales and product data were all transformed in one workflow, opening contribution to product, engineering and finance teams.
“We've grown incredibly in the last 2.5 years, and there's no way that growth would have been possible without bringing in Snowflake, dbt, Metaplane, and the modern data stack.”
BCBen CohenData Engineering Lead, SpotOn
The results, in context
After adopting dbt Cloud, SpotOn reduced time to actionable insights by 6x (a 600% decrease) and increased engineering contribution by 8.5x, growing from two to 17 contributors to its ETL code. The company reported $110,500 saved and at least 10 hours of team time saved every week, while building models went from taking days or weeks to hours.