The role involves owning the end-to-end testing strategy for Python-based data pipelines and machine learning workloads. The individual will ensure functional parity, data integrity, and model performance consistency during system migrations. Responsibilities include designing test frameworks for ETL, feature engineering, and inference pipelines. The role requires coordinating parallel runs and shadow execution with business subject matter experts. Additionally, the position involves driving defect triage, root cause analysis, and regression testing while governing documentation and compliance reporting.

The role requires eight to twelve years of experience in data or machine learning testing, with at least four years spent leading test teams. Candidates must possess hands-on proficiency in Python, Pandas, NumPy, and PyTest. Experience testing Azure ML pipelines, APIs, batch jobs, and data workflows is necessary. Furthermore, the position requires a strong understanding of statistical validation, model metrics, and DevOps practices.