Job Description

Salary: $122,100 - 162,800 per year Requirements:

• We look for 10+ years of experience in data, platform, or enterprise architecture within large-scale environments.
• We need proven experience designing and governing enterprise data platforms and architectures.
• We require hands-on experience with Azure Databricks, lakehouse architectures, and scalable data systems.
• We expect strong data modeling expertise and experience with cross-domain data integration.
• We value experience working in regulated settings with privacy, compliance, and governance demands.
• We look for expert knowledge of enterprise data architecture, data modeling, and cloud-native platforms.
• We require deep understanding of data governance, metadata management, lineage, and observability.
• We need solid knowledge of AI/ML data patterns, including RAG and vector retrieval architectures.
• We expect advanced proficiency in conceptual, logical, and physical data modeling methods.
• We prefer a bachelors degree or equivalent in Computer Science, Information Systems, Data Science, Engineering, or a related field.
• We value experience leading enterprise-wide architecture initiatives and shaping strategic direction.
• We prefer familiarity with enterprise information models, business glossaries, and semantic layers.
• We welcome exposure to Data Vault, dimensional modeling, or domain-driven design.
• We prefer hands-on experience with Unity Catalog, MLflow, Vector Search, and the Databricks ecosystem.
• We value Azure certifications such as AZ-305, AI-102, or AZ-500.

• We define and maintain the Azure Databricks reference architecture for AI/ML preparation, RAG grounding, orchestration, telemetry, and governance.
• We set and enforce platform standards and guardrails, including workspace patterns, Unity Catalog design, compute policies, and cost optimization practices.
• We evaluate and adopt emerging data and AI architecture patterns aligned to our enterprise strategy.
• We design and govern conceptual, logical, and physical data models for enterprise-scale platforms.
• We establish canonical data structures, shared business glossaries, and cross-domain standards to drive interoperability and reuse.
• We standardize modeling approaches across domains, including normalized, dimensional, Data Vault, and domain-driven design methods.
• We ensure data models support AI/ML, analytics, and operational use cases with consistency, traceability, and compliance.
• We standardize embedding, feature, vector, and contextual data design to support scalable RAG and AI use cases.
• We design secure integration patterns between Databricks and downstream AI services and applications.
• We partner with business and domain teams to turn capabilities into AI-ready, production-scale data assets.
• We ensure Unity Catalog acts as the system of record for data access, with fine-grained permissions, masking, lineage, and auditability.
• We apply secure-by-design and Zero Trust principles across all data and AI architectures.
• We govern the data lifecycle, including metadata standards, lineage, schema evolution, and versioning.
• We ensure compliance with regulatory, privacy, and data stewardship requirements.
• We embed quality engineering and validation into AI pipelines using MLflow, evaluation datasets, telemetry, and drift monitoring.
• We define production-readiness standards for workflows, monitoring, SLAs, and KTLO transitions.
• We continuously improve platform reliability, scalability, and observability.
• We serve as a lead technical authority across data architecture initiatives.
• We conduct architecture reviews and advise on standards, patterns, and best practices.
• We mentor and coach architects, engineers, and data professionals.
• We influence cross-functional teams and senior stakeholders to align architecture decisions with business outcomes.

• AI
• Architect
• Azure
• Cloud
• Data Vault
• Databricks
• Support
• Unity
• GameDev
• Security

More:

We are McKesson, an impact-driven Fortune 10 healthcare company that provides insights, products, and services to make quality care more accessible and affordable. We foster a culture where people can grow, make an impact, and contribute new ideas as we shape the future of health. This Lead Data Architect role is a senior individual contributor position focused on our Intelligent Data Platform, with emphasis on Azure Databricks, AI-ready data, and Retrieval-Augmented Generation capabilities. We offer a Flex and Connect work model with two days in the office each week, along with a competitive Total Rewards package that may include base pay, bonus, and long-term incentive opportunities. The posted base pay range for this role is $122,100 to $162,800.

last updated 32 week of 2026

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