Modern Data Stack Migration — Day 1: Scaling to 8+ Companies with DRY Architecture and Chasing a $2M Discrepancy

The first day of a Modern Data Stack migration involved transitioning from legacy spreadsheets and Qlik to a pipeline utilizing Python, ClickHouse, and dbt. The process focused on refactoring a maintenance-heavy setup where each company had duplicated scripts and separate .env files. By implementing a DRY architecture, the system was centralized into a single, parameterized extraction engine with a global .env file, enabling the infrastructure to scale efficiently across more than eight different companies.