Worked on the datafold/demo repository to implement a monthly scheduling rollout for monitors and data workflows, shifting from daily or frequent intervals to a standardized cadence on the first day of each month. This change involved updating YAML-based production job definitions and the data generation pipeline, ensuring that data freshness and alerting were maintained while reducing operational overhead. Leveraged skills in workflow automation, CI/CD, and DevOps to consolidate scheduling logic across multiple platforms, including BigQuery, Databricks, and Dremio. The approach improved resource optimization, enabled predictable scheduling, and enhanced maintainability by centralizing configuration changes in production YAML files.