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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Architect (Healthcare) - **Company:** McKesson - **Location:** Irving, TX, United States - **Experience:** Expert - **Salary:** $147,800.0 - $246,400.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Audit Trail, Microsoft Azure, Clinical Data Repository, Continuous Integration, Data Architecture, Data Dictionary, Data Governance, Extract Transform Load (ETL), Data Security, Data Systems, Relational Databases, DevOps, Amazon DynamoDB, Github, Interoperability, PostgreSQL, Meta-Data Management, Microsoft SQL Server, MongoDB, NoSQL, OAuth, OpenID, Oracle (Applications), Role-Based Access Control, Service-Oriented Architecture, Data Streaming, File Transfer Protocol (FTP), Cloud Platform System, Fast Healthcare Interoperability Resources, Multi-Cloud, Electronic Medical Records, Data Strategy, Data Lakes, Deployment Automation, Cassandra, Data Analytics, Health Level Seven International, Data Management, Databricks - **Published:** August 14, 2026 - **Apply:** https://mckesson.wd3.myworkdayjobs.com/en-US/External_Careers/job/USA-TX-Irving/Lead-Data-Architect--Healthcare-_JR0151564 ## About the Role * Degree or equivalent and typically requires 10+ years of relevant experience. Less years required if has relevant Master's or Doctorate qualifications. Critical Skills & Experience * 10+ years in technology roles with significant architecture experience in complex enterprises. * Cloud & Data Platforms: Expertise in Azure, Databricks, multi-cloud architectures, data lakes/lakehouses, real-time streaming, Unity Catalog, and modern data governance frameworks. Data Architecture & Engineering * Strong proficiency in data modeling techniques (conceptual, logical, physical) and experience with data modeling tools. * Advanced data modeling, normalization, ETL/ELT pipeline design, and batch/streaming architectures. * Experience with relational databases (SQL Server, Oracle, PostgreSQL) and NoSQL databases (MongoDB, Cassandra, DynamoDB). * Familiarity with data governance frameworks, data quality management, and master data management (MDM) principles. * Integration of external data sources, SFTP-based ETL, and real-time pipelines. * Experience integrating metadata and lineage into enterprise data governance platforms (e.g., Alation) to enable discoverability, auditability, and data quality across the organization. * Interoperability & Standards: SOA modernization, service-based architectures, * OAuth2/OIDC/SMART/RBAC/ABAC; deep understanding of healthcare data standards (HL7, FHIR, ICD-10) and HIPAA compliance. * AI & Analytics Enablement: Architecting ML/AI-ready environments and real-time analytics platforms. * DevOps & Platform Enablement: CI/CD pipelines, automated deployment, GitHub version control. * Healthcare Domain Expertise: EMR systems, claims processing, MDM, and IQVIA or similar healthcare datasets. Non-Technical Competencies * Ability to align diverse stakeholders around a clear and compelling technical vision. * Strong analytical skills to solve complex, cross-functional enterprise challenges. * Proven ability to balance business priorities, technical constraints, and risk management. * Excellent communicator capable of influencing audiences from engineers to senior executives. * Experience participating in and leading architecture review boards and defining reusable enterprise patterns. * Strategic mindset with the ability to guide long-term platform and capability evolution. * Demonstrates collaboration, accountability, and a team-first mindset. * Deep understanding of the healthcare industry, enterprise risk management, and regulatory considerations. * Proven ability to partner cross-functionally with Compliance, Privacy, and Governance stakeholders to drive enterprise data strategy and embed policy-driven governance controls into architecture designs. * Startup experience (2+ years) strongly preferred. This role is a hybrid position. The selected candidate is expected to work on-site at our Las Colinas office a minimum of two (2) days per week, with the remaining days worked remotely. Specific in-office days may be designated based on team needs and business priorities. McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role. Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g., H1B, O1, E3, H1B1, TN, F1 OPT, F1 STEM OPT, F1 CPT, etc.) now or in the future. ## Description * Architecture Leadership: Define technical strategy, architecture standards, and long term roadmap; lead design and planning for new platforms, products, and services; establish enterprise-wide best practices and reusable patterns. * Technology Innovation & Delivery: Oversee architectural execution of enterprise scale data solutions * Evaluate emerging technologies and recommend innovative, business-aligned solutions; mentor teams on modern architecture and cloud-native practices. * Governance, Security & Compliance: Provide technical governance through architecture review boards and standards enforcement * Ensure compliance with healthcare regulations and enterprise security standards; embed data security, privacy, and regulatory compliance in all data architecture designs. * Partner closely with Compliance, Privacy, and Enterprise Governance teams to define and execute a holistic data strategy aligned with regulatory requirements and enterprise risk posture. * Data Strategy & Governance Integration: Work in close collaboration with Data * Governance organizations to operationalize metadata management and lineage by integrating enterprise data assets with governance platforms such as Alation. * Ensure consistent capture, enrichment, and stewardship of metadata across data platforms to support discoverability, lineage, data quality, and auditability. * Documentation & Standards: Develop and maintain comprehensive documentation of data architecture, data dictionaries, and data flow diagrams; ensure consistency, traceability, and quality across platforms. 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