Case Study: Zippi future-proofs its data platform with Dagster Labs

Zippi successfully navigated a common growth milestone, future-proofing data operations on Dagster

Zippi, a Brazilian fintech startup, faced challenges scaling its data operations as it grew. Their initial linear data pipelines, built on tools like dbt and Hevo, were unable to dynamically integrate their proprietary machine learning model for loan underwriting. This created data silos, hindered collaboration between teams, and made pipelines difficult to troubleshoot. They turned to Dagster to build a centralized and reliable data platform.

By adopting Dagster incrementally, Zippi first operationalized its critical ML model within the orchestrator. The team then used Dagster to unify their entire data stack, replacing custom scripts with a single platform for end-to-end orchestration and observability. This solution provided greater visibility into data assets, made pipelines far easier to troubleshoot, and reduced maintenance costs. Dagster enabled Zippi to deliver insights faster with less downtime, future-proofing their data operations as the company continues to grow.

Zippi

Renan Veras

Data Engineer