What skills or team roles are required to operate EASL day-to-day?

Most organizations rely on a combination of data engineers and analysts or operations staff to manage EASL. Because workflows are configured rather than coded, teams spend less time writing scripts and more time refining logic, validating data, adding new use cases, and beyond. EASL is designed to reduce the burden on senior engineering talent; day-to-day management often shifts to roles that focus on data quality, operations, or platform administration.