About this job
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<strong>Headquarters:</strong> Remote
<br /><strong>URL:</strong> <a href="https://www.toptal.com/">https://www.toptal.com/</a>
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<h2>About the Role</h2>
<p>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.</p>
<h2>What You'll Do</h2>
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<p>Review the current forecasting platform architecture and identify areas for improvement</p>
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<p>Refactor existing Databricks, Python, and PySpark implementations</p>
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<p>Move business logic out of Databricks notebooks and into reusable Python modules or packages</p>
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<p>Improve separation of concerns between orchestration and core business logic</p>
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<p>Establish stronger engineering standards and help define what "good" looks like for the platform</p>
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<p>Implement or improve automated testing practices and validation mechanisms for forecasting workflows</p>
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<p>Build or improve monitoring and observability, increasing visibility into how predictions are generated</p>
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<p>Help monitor model behavior and operational health over time</p>
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<p>Improve reliability of scheduled training workflows, reducing manual intervention on failure</p>
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<p>Improve failure handling, retries, and overall workflow resilience</p>
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<p>Maintain and extend existing forecasting capabilities as needed</p>
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<h2>What You Bring</h2>
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<p>Strong professional experience with Databricks, including workspaces, notebooks, scheduled workflows, and CI/CD processes</p>
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<p>Strong Python engineering experience, including designing reusable modules or packages</p>
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<p>Strong PySpark experience with production data pipelines or distributed data processing</p>
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<p>Experience refactoring production code and improving maintainability</p>
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<p>Familiarity with time series forecasting concepts and workflows</p>
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<p>Ability to understand and work effectively within an existing, unfamiliar codebase</p>
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<p>Experience improving software quality, testing strategy, and engineering standards</p>
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<p>Experience implementing automated testing practices</p>
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<p>Experience improving monitoring, observability, or operational visibility for production systems</p>
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<p>Strong judgment around technical debt, refactoring priorities, and maintainable architecture</p>
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<p>Ability to work with existing systems rather than only building from scratch</p>
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<h2>Why This Role</h2>
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<p>Real production impact: Improve a system the business already relies on, not a proof-of-concept</p>
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<p>Engineering maturity focus: Bring testing, observability, and maintainability to a platform that's outgrown its current state</p>
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<p>Meaningful ownership: Help define engineering standards for the forecasting platform going forward</p>
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<p>Flexible location: Preference for Toronto or St. Louis, but open to remote consultants globally with North American working-hours overlap</p>
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<h2>How to Apply</h2>
<p>Ready to bring engineering rigor to a production forecasting platform? Apply through Toptal here: https://www.toptal.com/talent/apply</p>
<p><strong>To apply:</strong> <a href="https://weworkremotely.com/remote-jobs/toptal-senior-data-ml-engineer-databricks-forecasting-platform-remote">https://weworkremotely.com/remote-jobs/toptal-senior-data-ml-engineer-databricks-forecasting-platform-remote</a></p>