combine priority internal and external data sources, understanding quality, permissions and fitness for use. Design, build and operate reliable pipelines in Microsoft Fabric and Databricks to ingest, clean, standardise, enrich, version and publish structured, semi-structured and unstructured data as reusable data assets. Create scalable lakehouse data models, schemas, data … clients, organisations, people, matters, sectors, jurisdictions, opportunities and legal topics. Implement data-quality checks, lineage, provenance, observability, monitoring and change management within Fabric and Databricks workflows so data assets remain trusted over time. Conduct exploratory data analysis to surface patterns, gaps, anomalies and data-quality issues, and identify opportunities ...