Case Study: Slack achieves timely, scalable analytics and empowers employees to innovate with Matillion ETL for Snowflake

With Matillion ETL and Snowflake, Slack reduced the time needed to create critical revenue metrics from up to 6 hours to just 30 minutes

Slack, the collaboration software company, was held back by a legacy data architecture that produced stale business-system datasets (often ~30 hours old) and required heavy Airflow/Python scripting to maintain. To modernize its analytics stack, Slack chose Snowflake and Looker and adopted Matillion’s product, Matillion ETL for Snowflake, to address slow, resource‑intensive ETL and enable faster access to accurate data.

Matillion delivered a Snowflake-native ETL solution using pre-built connectors and reusable components to consolidate workflows and pull data from sources like Salesforce, Workday, Pardot, Google Analytics, Facebook, and Greenhouse. With Matillion ETL for Snowflake, Slack cut time to create critical revenue metrics from up to 6 hours to 30 minutes, reduced custom code and maintenance so a two-person team can run the stack, met executive SLAs for timely data, and empowered employees to innovate with faster, scalable analytics.

Slack

Vamsee Kata

Manager, Platform Architecture & Ops Simplicity Speed Scale Savings