McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare, focusing on quality care for patients, communities, and people. Our Decision Intelligence (DI) team is looking for a Senior / Lead Platform Architect to define and govern the Azure Databricks platform patterns for AI-ready data and RAG across the enterprise, including Unity Catalog access controls, secure retrieval, evaluation/telemetry standards, and production readiness guardrails. As part of the DI team, you will lead the design of an AIready ''Intelligent Data Platform'' ensuring consistent, governed, interoperable data across McKessons platforms and BU segments. Key Roles & Responsibilities Define and maintain the Azure Databricks reference architecture for AI data preparation, grounding (RAG), orchestration, telemetry, and governance. Establish Databricks platform standards and guardrails, including workspace patterns, Unity Catalog design, compute policies, and cost controls. Ensure Unity Catalog is the system of record for AI data access, enforcing finegrained permissions, data masking, lineage, and auditability. Standardize embedding, feature, and context management to enable reuse of AIready data assets across use cases. Operate AI intake and onboarding for Databricks workloads, ensuring proper classification, governance routing, and dependency alignment. Architect secure integration patterns between Databricks and downstream AI services or applications, preventing unapproved data egress. Embed quality engineering into AI pipelines using MLflow, evaluation datasets, telemetry, and drift monitoring before production rollout. Ensure production readiness and operability of Databricks AI workloads through Jobs/Workflows standards, monitoring, and KTLO handoff. Apply AI security and compliance by design within Databricks, including identity enforcement, sensitive data protection, and audit logging. Enable delivery teams through Databricksspecific playbooks, templates, and coaching to accelerate compliant AI adoption. Minimum Requirements Degree or equivalent & typically requires 10+ years of relevant experience. Required Qualifications 7+ years in platform, solution, or enterprise architecture with handson experience in Azure Databricks. Proven experience designing AI/analytics data platforms, including governance, security, and largescale data access patterns. Strong understanding of RAG, vector retrieval, data governance, and observability in production environments. Experience working in regulated environments with security, privacy, and compliance requirements. Preferred Qualifications Experience enabling GenAI or agentic use cases on Databricks. Familiarity with Unity Catalog, MLflow, Vector Search, and Azurenative security patterns. Azure certifications (AZ 305, AI 102, AZ 500) strongly preferred. Working Conditions Inoffice requirement: 2 days a week in an office location (flexible schedule). McKesson offers a competitive compensation package, including base pay, potential annual bonuses; additional compensation such as longterm incentive opportunities may be offered. Benefits and details are available on our career site. Equal Employment Opportunity McKesson is an Equal Opportunity Employer and provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on our full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers, including those with disabilities. If you need a reasonable accommodation, please contact the appropriate disability accommodation contact; resumes or CVs submitted by email will not be accepted. #J-18808-Ljbffr
Job Title
Senior / Lead Platform Architect