Own the Python engine layer for algorithms and data processing
Process large volumes of operational schedule data through constraint evaluation
Generate periodic staff rosters by solving constraint problems
Real-time task assignment using proximity scoring against live employee location data
Scheduled KPI aggregation and SLA scoring across all modules

5 or more years of Python backend or data engineering experience
Experience with constraint solving, optimization, or scheduling algorithms (OR-Tools, PuLP, or equivalent)
Strong data processing experience with large datasets (Polars, pandas, or Apache Spark)
Experience with task queues and async processing (Celery, RQ, or equivalent)
Familiarity with Azure
Comfortable working with SQL databases and writing performant queries
Experience consuming REST APIs and message queues
Experience with Azure Functions or equivalent serverless compute
Experience with OR-Tools specifically
Knowledge of scikit-learn or ML model integration (ONNX, Azure ML) for a future ML upgrade path
Experience with Pydantic for data validation and schema enforcement
Experience with large-scale workforce management or scheduling systems
Familiarity with SLA-based operational frameworks
Experience working in fast-paced, operationally critical environments

Data Engineer, Python

Key skills