embed validation, completeness, timeliness, reconciliation, and exception controls into core workflows. Work with Data Modelling to ensure pipelines support agreed entities, identifiers, relationships, taxonomies, metadata, and lifecycle rules. Ensure datasets are delivered with clear ownership, controls, lineage, documentation, support models, and auditability. Improve monitoring, alerting, root-cause analysis, recovery processes … data handling, enrichment, validation, exception management, monitoring, and recovery processes. Support vendor- and platform-driven change, including schema changes, API migrations, delivery format changes, taxonomy updates, and workflow migrations. Identify practical opportunities to use AI-assisted tooling and automation to reduce manual mapping, validation, documentation, exception handling, and operational triage ...