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Senior Data/ML Engineer — Databricks Forecasting Platform | Remote at Toptal. Location Information: Anywhere in the World. . . Headquarters:. Remote . URL:. . https://www.toptal.com/. . . About the Role. . We're looking for a Senior Data/ML Engineer to refactor, operationalize, and improve an existing time series forecasting platform that's already live and driving real business value. This is not a greenfield build — the focus is modernizing a Databricks-based forecasting system that's been maintained primarily by a single developer for years. You'll reduce technical debt, strengthen testing and observability, and raise the engineering bar on a system the business already depends on. If you'd rather bring discipline and maturity to an existing production system than start from a blank slate, this is built for that.. . What You'll Do. . . . Review the current forecasting platform architecture and identify areas for improvement. . . . Refactor existing Databricks, Python, and PySpark implementations. . . . Move business logic out of Databricks notebooks and into reusable Python modules or packages. . . . Improve separation of concerns between orchestration and core business logic. . . . Establish stronger engineering standards and help define what "good" looks like for the platform. . . . Implement or improve automated testing practices and validation mechanisms for forecasting workflows. . . . Build or improve monitoring and observability, increasing visibility into how predictions are generated. . . . Help monitor model behavior and operational health over time. . . . Improve reliability of scheduled training workflows, reducing manual intervention on failure. . . . Improve failure handling, retries, and overall workflow resilience. . . . Maintain and extend existing forecasting capabilities as needed. . . . What You Bring. . . . Strong professional experience with Databricks, including workspaces, notebooks, scheduled workflows, and CI/CD processes. . . . Strong Python engineering experience, including designing reusable modules or packages. . . . Strong PySpark experience with production data pipelines or distributed data processing. . . . Experience refactoring production code and improving maintainability. . . . Familiarity with time series forecasting concepts and workflows. . . . Ability to understand and work effectively within an existing, unfamiliar codebase. . . . Experience improving software quality, testing strategy, and engineering standards. . . . Experience implementing automated testing practices. . . . Experience improving monitoring, observability, or operational visibility for production systems. . . . Strong judgment around technical debt, refactoring priorities, and maintainable architecture. . . . Ability to work with existing systems rather than only building from scratch. . . . Why This Role. . . . Real production impact: Improve a system the business already relies on, not a proof-of-concept. . . . Engineering maturity focus: Bring testing, observability, and maintainability to a platform that's outgrown its current state. . . . Meaningful ownership: Help define engineering standards for the forecasting platform going forward. . . . Flexible location: Preference for Toronto or St. Louis, but open to remote consultants globally with North American working-hours overlap. . . . How to Apply. . Ready to bring engineering rigor to a production forecasting platform? Apply through Toptal here: https://www.toptal.com/talent/apply. . To apply:. . https://weworkremotely.com/remote-jobs/toptal-senior-data-ml-engineer-databricks-forecasting-platform-remote.