data engineering teams to implement scalable data lakehouse oriented feature architectures and enterprise‐grade ML governance. Champion engineering standards for model quality, documentation, observability, and platform resilience. Feature Engineering & Data Architecture Architect highly scalable, production‐ready feature pipelines within Lakehouse environments. Set the technical direction for fallback and resilience strategies … including scoring metrics, latency, error analytics, and SLOs. Partner with platform teams to optimise cost, scale, and reliability of inference endpoints. Monitoring, Drift Detection & Observability Define observability standards for feature drift, concept drift, performance degradation, and data integrity. Lead the creation of dashboards, benchmarks, and automated alerting across ...