• Design and evolve a scalable, secure, cloud-native lakehouse platform leveraging Databricks, Microsoft Fabric (OneLake, Lakehouse, Data Factory), and dbt. • Define modeling patterns, governance frameworks, and engineering best practices across the data lifecycle. • Lead design reviews and guide teams in adopting scalable architectural patterns. • Drive long-term platform strategy and evaluate emerging technologies. • Design and implement batch and streaming data pipelines for healthcare data sources (EHR, claims, HL7/FHIR, APIs, flat files, databases). • Develop modular ingestion, quality, lineage, metadata, and observability frameworks that scale across domains. • Produce clean, analytics-ready datasets and data models for BI, analytics, and machine learning workloads. • Implement HIPAA-aligned access patterns and secure handling of PHI. • Architect Databricks workloads (clusters, jobs, Unity Catalog, Delta Lake) for reliability, performance, and cost efficiency. • Integrate Databricks and Microsoft Fabric with Azure services and enterprise systems. • Partner with product managers, data scientists, analysts, clinicians, and business stakeholders to translate healthcare data needs into scalable solutions. • Lead cross-functional initiatives that modernize and unify the organization’s data ecosystem. • Mentor senior and mid-level engineers; elevate team capability through technical coaching and standards. • Drive roadmap planning, platform evolution, and long-term data strategy. • Champion engineering excellence, reliability practices, documentation quality, and governance.