IT Director, Data & AI Architecture

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 115,000 colleagues serve people in more than 160 countries.

     

JOB DESCRIPTION:

About Abbott

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans diagnostics, medical devices, nutrition, and branded generic medicines. With 115,000 colleagues serving people in more than 160 countries, Abbott is committed to advancing healthcare through innovation, data, and technology.

The Opportunity

Reporting to the Director of Information Management, Data & Analytics, the Data & AI Architect will play a critical role in defining and delivering Abbott's enterprise data and AI architecture vision. This leader will architect scalable, secure, and AI-ready data platforms, enable advanced analytics and AI use cases, and establish the technical standards that support Abbott's transition to a modern data ecosystem.

The Data & AI Architect will serve as the principal technical authority across data platforms, data products, analytics, integration patterns, and AI enablement capabilities. Working closely with Data Engineering, AI Engineering, Enterprise Architecture, Security, and business stakeholders, this role will ensure Abbott's data estate supports current operational needs while accelerating innovation in analytics, automation, and artificial intelligence.

What You'll Work On

Enterprise Data & AI Architecture

• Define and maintain the enterprise data and AI reference architecture aligned with Abbott's Information Management and AI strategy.
• Develop future-state architecture blueprints supporting Data Mesh, Data Fabric, cloud-native analytics platforms, and AI-enabled business capabilities.
• Establish architecture principles, standards, patterns, and governance frameworks for enterprise data and AI solutions.
• Partner with Enterprise Architecture to ensure alignment between business, application, data, and technology architectures.
• Evaluate emerging technologies, industry trends, and AI capabilities and translate them into practical adoption roadmaps.

Data Platform Architecture

• Design scalable and secure cloud-native data platforms leveraging technologies such as Snowflake, Databricks, Microsoft Fabric, Azure Data Services, and related ecosystem tools.
• Define architecture standards for ingestion, transformation, storage, orchestration, observability, metadata management, and data sharing.
• Establish design patterns supporting structured, semi-structured, streaming, and unstructured data workloads.
• Define architectural approaches for Infrastructure-as-Code, platform automation, containerization, and CI/CD enablement.
• Partner with platform and engineering teams to optimize scalability, resiliency, performance, and cost management.

Data Integration & Data Products

• Define enterprise integration patterns supporting batch, near real-time, API-driven, and event-driven architectures.
• Establish standards for data contracts, domain ownership, interoperability, and Data Product lifecycle management.
• Drive implementation of reusable data assets and federated Data Mesh principles across Abbott business domains.
• Ensure data products are discoverable, documented, governed, and aligned with business and AI consumption requirements.
• Partner with business units to translate strategic priorities into scalable information architectures.

AI & Advanced Analytics Enablement

• Architect AI-ready data ecosystems supporting machine learning, generative AI, predictive analytics, and agent-based solutions.
• Design foundational capabilities including feature stores, vector databases, semantic layers, knowledge repositories, and Retrieval-Augmented Generation (RAG) architectures.
• Establish architectural standards for model training data, feature engineering, metadata, lineage, and model operationalization.
• Collaborate with AI Engineering and Automation teams to ensure secure and scalable integration of AI services into enterprise workflows.
• Lead data readiness and AI architecture assessments for strategic AI investments and initiatives.

Cloud & Digital Platform Strategy

• Partner with Cloud Infrastructure, Enterprise Architecture, and Security leaders to define and evolve Abbott's hybrid-cloud and multi-cloud strategy, ensuring alignment with enterprise technology, data, and AI ob