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 - Solid 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

📌 Senior Data/ML Engineer — Databricks Forecasting Platform | Remote (Toronto)
🏢 Neura Market
📍 Toronto