Principal IT Data Architect - Snowflake, Data Governance & AI Platforms

Careers that change lives start here. Medtronic is a global leader in healthcare technology with a Mission to alleviate pain, restore health, and extend life. Our 95,000 employees work across more than 150 countries to put patients first — developing innovative medical technologies that improve the lives of 72+ million patients each year. Your unique talents will help shape the future of healthcare while building a career grounded in purpose, growth, and impact. A Day in the Life The Principal IT Data Architect is responsible for defining and leading the organization's data architecture strategy to ensure data is secure, reliable, scalable, and accessible for business operations, analytics, and AI initiatives. This role designs enterprise data solutions, establishes data standards and governance practices, and works closely with business and technology teams to enable data-driven decision-making. The Principal IT Data Architect provides technical leadership, drives innovation in data platforms and integrations, and ensures alignment between data architecture and business goals. Responsibilities may include the following and other duties may be assigned. Define and maintain the enterprise data architecture strategy, standards, and roadmap. Design conceptual, logical, and physical data models supporting commercial business processes. Establish architecture principles, patterns, and best practices that improve scalability, performance, and operational efficiency. Evaluate and approve solution designs to ensure alignment with enterprise architecture standards. Lead the architecture and evolution of enterprise cloud data platforms, with a focus on Snowflake. Design modern data lakehouse architectures, semantic layers, and data consumption frameworks. Drive adoption of advanced platform capabilities supporting analytics, AI, and business intelligence. Ensure platforms meet performance, reliability, scalability, security, and cost optimization objectives. Design enterprise data integration frameworks connecting business applications, analytics platforms, and external data sources. Define standards for ETL/ELT processes, APIs, event-driven architectures, and real-time data movement. Establish and promote best practices for data governance, metadata management, data quality, and master data management. Ensure data lineage, traceability, consistency, and compliance requirements are effectively addressed. Enable enterprise reporting, analytics, AI, and machine learning initiatives through robust data architecture. Partner with business, analytics, and data science teams to develop scalable and reusable data products. Define architecture patterns supporting advanced analytics, Generative AI, and intelligent automation capabilities. Translate business objectives into scalable data solutions that drive meaningful outcomes. Design secure data architectures that comply with global privacy, security, and regulatory requirements.