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