Lead Data Architect - Data & AI Platform

Responsibilities

• Platform Architecture & Strategy
• Define and maintain the Azure Databricks reference architecture supporting AI/ML data preparation, RAG grounding, orchestration, telemetry, and governance
• Establish and enforce platform standards and guardrails, including workspace patterns, Unity Catalog design, compute policies, and cost optimization strategies
• Lead evaluation and adoption of emerging data and AI architecture patterns aligned to enterprise strategy
• Data Modeling & Information Architecture
• Define and govern conceptual, logical, and physical data models for enterprise-scale platforms
• Establish canonical data structures, business glossaries, and cross-domain standards ensuring interoperability and reuse
• Standardize modeling approaches (e.g., normalized, dimensional, Data Vault, domain-driven design) across domains
• Ensure data models support AI/ML, analytics, and operational use cases with consistency, traceability, and compliance
• AI & Data Platform Enablement
• Standardize embedding, feature, vector, and contextual data design to enable scalable RAG and AI use cases
• Design secure and governed integration patterns between Databricks and downstream AI services and applications
• Partner with business and domain teams to translate capabilities into AI-ready, production-scale data assets
• Governance, Security & Compliance
• Ensure Unity Catalog serves as the system of record for data access, enforcing fine-grained permissions, masking, lineage, and auditability
• Apply secure-by-design and Zero Trust principles to all data and AI architectures
• Govern data lifecycle management, including metadata standards, lineage, schema evolution, and versioning
• Ensure compliance with regulatory, privacy, and data stewardship requirements
• Operational Excellence & Quality Engineering
• Embed quality engineering and validation into AI pipelines using MLflow, evaluation datasets, telemetry, and drift monitoring
• Define standards for production readiness including workflows, monitoring, SLAs, and KTLO transitions
• Drive continuous improvement in platform reliability, scalability, and observability
• Technical Leadership & Influence (P5 Expectations)
• Act as a lead technical authority across data architecture initiatives
• Conduct architecture reviews and provide guidance on standards, patterns, and best practices
• Mentor and coach architects, engineers, and data professionals
• Influence cross-functional teams and senior stakeholders to align architecture to business outcomes
• Minimum Job Qualifications (Knowledge, Skills, & Abilities)
• Expert knowledge of enterprise data architecture, data modeling, and cloud-native platforms
• Deep expertise in data governance, metadata management, lineage, and observability
• Strong understanding of AI/ML data patterns including RAG and vector retrieval architectures
• Advanced proficiency in conceptual, logical, and physical data modeling techniques
• Experience designing secure, scalable Azure-based data platforms (Databricks preferred)
• Ability to define and communicate architecture standards, roadmaps, and strategies
• Strong skills in stakeholder engagement, influencing, and cross-functional collaboration
• Excellent written and verbal communication skills for technical and executive a

Benefits

Additional Information

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. Position Summary The Lead Data Architect - Data & AI Platform provides enterprise technical leadership to define, govern, and evolve McKesson's Intelligent Data Platform, with a focus on Azure Databricks, AI-ready data, and Retrieval-Augmented Generation (RAG) capabilities. This role operates as a senior individual contributor and recognized subject matter expert, responsible for establishing architecture standards, platform patterns, and data modeling strategies that enable secure, scalable, and compliant data and AI solutions across the enterprise. The Lead Data Architect drives cross-domain alignment through canonical data models and shared data structures, ensuring consistency and interoperability across business units and platforms. This role partners closely with engineering, analytics, and business teams to translate complex capabilities into reusable, AI-ready data assets. As a key technical leader, this role influences enterprise data strategy, guides solution design, mentors architects and engineers, and ensures architectural decisions deliver measurable business impact in a regulated healthcare environment.

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