Senior Data ML Engineer — Databricks Forecasting Platform Remote

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