About the Role
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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
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* 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
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* 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
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* 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
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Ready to bring engineering rigor to a production forecasting platform? Apply through Toptal here: https://www.toptal.com/talent/apply