We anticipate the application window for this opening will close on - 9 Feb 2026

 

At Medtronic you can begin a life-long career of exploration and innovation, while helping champion healthcare access and equity for all. You’ll lead with purpose, breaking down barriers to innovation in a more connected, compassionate world.

A Day in the Life

The Data & AI Architect is responsible for designing, governing, and evolving the enterprise data and AI ecosystem. This role provides strategic and technical leadership across data engineering, analytics, AI/ML, and cloud platform architecture. As the primary architecture expert for Data & Analytics, the architect defines future-state architectures, represents the D&A organization in the Architecture Review Board (ARB), and ensures that all new solutions are secure, scalable, compliant, and aligned with business strategy. This role requires deep hands-on technical expertise, strong architectural judgment, and the ability to influence teams across the organization.

This position is an exciting opportunity to work with Medtronic's Diabetes business. Medtronic has announced its intention to separate the Diabetes division to promote future growth and innovation within the business and reallocate investments and resources across Medtronic, subject to applicable information and consultation requirements. This separation provides our team with a bold opportunity to unleash our potential, enabling us to operate with greater speed and agility. As a separate entity, we anticipate leveraging increased investments to drive meaningful innovation and enhance our impact on patient care.

Responsibilities may include the following and other duties may be assigned.

Enterprise Data & AI Architecture Leadership

• Define the enterprise data and AI architecture aligned with business and platform strategy.

• Establish reference architectures for data platforms, analytics, ML/GenAI, metadata, governance, and integrations.

• Drive cloud-first, scalable, cost-optimized architecture across AWS/Azure/GCP.

• Represent D&A in the Architecture Review Board (ARB), reviewing, approving, and influencing architecture decisions across the company.

Data Platform & Engineering

• Architect modern data platforms including data lakehouses, data warehouses, and real-time streaming systems.

• Lead standards for ingestion, ETL/ELT, orchestration, automation, and data modeling.

• Ensure platform reliability, performance, and readiness for enterprise-scale analytics and AI.

AI/ML Platform & Solution Architecture

• Design end-to-end ML and GenAI architectures including MLOps/LLMOps pipelines, feature stores, vector databases, monitoring, and deployment frameworks.

• Lead solution architecture for AI products and platforms—from feasibility and design through deployment.

• Guide engineering teams by providing best practices for responsible, secure, and scalable AI implementation.

• Run POCs, evaluate emerging AI technologies (RAG, agentic frameworks), and drive adoption across domains.

Data Governance, Security & Compliance

• Knowledge on governance frameworks, data standards, lineage, quality patterns, and security models.

• Ensure compliance with regulatory requirements (GDPR, HIPAA, FDA, SOX, etc.).

• Apply security frameworks and safe AI patterns to ensure responsible AI in production.

Integration & Interoperability

• Architect API, event-driven, streaming, and microservices integration patterns.

• Ensure seamless interoperability between operational systems (SAP, Salesforce) and analytics/AI platforms.

Solution Design & Technical Delivery

• Translate business requirements into scalable, secure, cloud-native architectures.

• Develop architecture diagrams, data flows, canonical models, and integration patterns.

• Oversee solution delivery across engineering and product teams, ensuring alignment to enterprise standards and ARB guidance.

Cross-Functional Leadership & Collaboration

• Act as a trusted advisor to engineering, product, data science, BI/analytics, and security teams.

• Mentor engineers; uplift architectural maturity across teams.

• Communicate complex architecture to senior leaders and non-technical stakeholders.

• Champion adoption of AI-first development practices across the organization.

Operational Excellence & Innovation

• Lead capacity planning, performance t