Senior Data/ML Engineer — Databricks Forecasting Platform | Remote

About this role

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: Open www.toptal.com/talent/apply To apply: Open weworkremotely.com/remote-jobs/toptal-senior-data-ml-engineer-databricks-forecasting-platform-remote