Senior / Lead Platform Architect

About

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 design of AI ready “Intelligent Data Platform” ensuring consistent, governed, interoperable data across McKesson's platforms and BU segments.

Key Roles & Responsibilities

Platform Architecture Leadership

• 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 fine grained permissions, data masking, lineage, and auditability.
• Standardize embedding, feature, and context management to enable reuse of AI ready 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 Databricks specific playbooks, templates, and coaching to accelerate compliant AI adoption.

Minimum Requirement

Degree or equivalent and typically requires 10+ years of relevant experience

Required Qualifications

• 7+ years in platform, solution, or enterprise architecture with hands on experience in Azure Databricks.
• Proven experience designing AI/analytics data platforms, including governance, security, and large scale 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 Azure-native security patterns.
• Azure certifications (AZ 305, AI 102, AZ 500) strongly preferred.

Working Conditions

• In office requirement, we are Flex and Connect with 2 days a week in office