Position SummaryThe 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.Key ResponsibilitiesPlatform Architecture & StrategyDefine and maintain the Azure Databricks reference architecture supporting AI/ML data preparation, RAG grounding, orchestration, telemetry, and governanceEstablish and enforce platform standards and guardrails, including workspace patterns, Unity Catalog design, compute policies, and cost optimization strategiesLead evaluation and adoption of emerging data and AI architecture patterns aligned to enterprise strategyData Modeling & Information ArchitectureDefine and govern conceptual, logical, and physical data models for enterprise-scale platformsEstablish canonical data structures, business glossaries, and cross-domain standards ensuring interoperability and reuseStandardize modeling approaches (e.G., normalized, dimensional, Data Vault, domain-driven design) across domainsEnsure data models support AI/ML, analytics, and operational use cases with consistency, traceability, and complianceAI & Data Platform EnablementStandardize embedding, feature, vector, and contextual data design to enable scalable RAG and AI use casesDesign secure and governed integration patterns between Databricks and downstream AI services and applicationsPartner with business and domain teams to translate capabilities into AI‑ready,



production‑scale data assetsGovernance, Security & ComplianceEnsure Unity Catalog serves as the system of record for data access, enforcing fine‑grained permissions, masking, lineage, and auditabilityApply secure‑by‑design and Zero Trust principles to all data and AI architecturesGovern data lifecycle management, including metadata standards, lineage, schema evolution, and versioningEnsure compliance with regulatory, privacy, and data stewardship requirementsOperational Excellence & Quality EngineeringEmbed quality engineering and validation into AI pipelines using MLflow, evaluation datasets, telemetry, and drift monitoringDefine standards for production readiness including workflows, monitoring, SLAs, and KTLO transitionsDrive continuous improvement in platform reliability, scalability, and observabilityTechnical Leadership & Influence (P5 Expectations)Act as a lead technical authority across data architecture initiativesConduct architecture reviews and provide guidance on standards, patterns, and best practicesMentor and coach architects, engineers, and data professionalsInfluence cross‑functional teams and senior stakeholders to align architecture to business outcomesMinimum Job QualificationsExpert knowledge of enterprise data architecture, data modeling, and cloud‑native platformsDeep expertise in data governance, metadata management, lineage, and observabilityStrong understanding of AI/ML data patterns including RAG and vector retrieval architecturesAdvanced proficiency in conceptual, logical, and physical data modeling techniquesExperience designing secure, scalable Azure‑based data platforms (Databricks preferred)Ability to define and communicate architecture standards, roadmaps, and strategiesStrong skills in stakeholder engagement, influencing, and cross‑functional collaborationExcellent written and verbal communication skills for technical and executive audiencesRequired Qualifications10+ years of experience in data, platform,



or enterprise architecture within large‑scale environmentsProven experience designing and governing enterprise data platforms and architecturesHands‑on experience with Azure Databricks, data lakehouse architectures, and scalable data systemsStrong experience in data modeling and cross‑domain data integrationExperience working in regulated environments with compliance, privacy, and governance requirementsPreferred QualificationsExperience defining enterprise information models, business glossaries, and semantic layersFamiliarity with data modeling methodologies such as Data Vault, dimensional modeling, or domain‑driven designHands‑on experience with Unity Catalog, MLflow, Vector Search, and Databricks ecosystemExperience integrating data platforms with metadata, lineage, and governance toolsAzure certifications such as AZ‑305, AI‑102, or AZ‑500Business ExperienceBachelor’s degree or equivalent in Computer Science, Information Systems, Data Science, Engineering, or related fieldTypically requires 10+ years of relevant qualified experience in data architecture or related disciplinesDemonstrated ability to lead enterprise‑wide architecture initiatives and influence strategic directionExperience operating within regulated industries (e.G., healthcare, pharma, life sciences) preferredWork Model / Physical RequirementsWe are Flex and Connect with 2 days a week in officeBase Pay Range$122,100 - $162,800Equal Employment OpportunityMcKesson 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 McKesson’s 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 job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) [email protected] or (Canada) [email protected]. Resumes or CVs submitted to this email box will not be accepted.#J-18808-Ljbffr

📌 Lead Data Architect – Data & Ai Platform - $122,100 - $162,800 A Year (Winnipeg)
🏢 McKesson
📍 Winnipeg