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

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

Robust 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

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