IT Director, Data & AI Architecture
Job Location:
Waukegan, IL - USA
Yearly Salary:
Posted:
Application Deadline:
Vacancies:
Job Summary
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 115000 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 this person will play a critical role in defining and delivering Abbotts 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 Abbotts transition to a modern data ecosystem.
The IT Director Data and AI Architecture serves as Abbotts principal technical authority for enterprise data architecture cloud data platforms AI-ready ecosystems and modern data engineering. This individual is expected to operate as the senior-most data architecture leader guiding architectural strategy reviewing solution designs mentoring architects and engineers and driving key technology decisions across Abbotts enterprise data landscape.
This leader will establish the technical blueprint for Abbotts next-generation data platforms ensuring scalable secure high-performing and AI-ready architectures that accelerate analytics automation and artificial intelligence initiatives across the enterprise.
This person serves as a technical authority for Enterprise Data Architecture and AI programs providing guidance governance and decision-making support across the organization. We are seeking someone with the ability to define challenge and influence architectural standards strategies and technology roadmaps.
Functions as a senior hands-on technical leader and trusted advisor rather than a people manager. Acts as the primary go-to expert for complex architectural decisions and technology challenges. Drives and influences key technology and architecture decisions to ensure alignment with business objectives scalability and innovation goals.
What Youll Work On
Technical Architecture Leadership
Lead architecture reviews for major data and analytics initiatives.
Serve as a trusted technical advisor to engineering architecture and business leaders on enterprise data strategy and architecture decisions.
Define reference architectures and implementation standards for Snowflake Databricks Microsoft Fabric Azure Data Services and related cloud technologies.
Drive architectural decisions related to data lakehouse design medallion architectures semantic layers metadata services data observability vector databases and enterprise AI platforms.
Define enterprise information architecture canonical data models domain ownership boundaries and data product standards that support interoperability scalability and AI consumption.
Review and challenge engineering designs to ensure scalability resiliency performance maintainability and cost optimization.
Partner directly with engineering teams to solve complex technical architecture challenges and accelerate delivery of strategic initiatives.
Chair architecture review boards and provide final architecture recommendations for critical data analytics and AI investments.
Maintain hands-on awareness of modern data engineering cloud analytics and AI technologies.
Design enterprise-scale lakehouse architectures utilizing Databricks Delta Lake Apache Iceberg Snowflake and cloud-native storage platforms.
Data Engineering & Platform Architecture
Define architecture standards for data ingestion transformation orchestration observability DataOps CI/CD and platform automation.
Establish patterns supporting structured semi-structured streaming and unstructured data workloads.
Define enterprise integration standards leveraging APIs event-driven architectures messaging platforms and real-time data processing.
Guide implementation of Infrastructure as Code (IaC) platform engineering containerization and automated deployment practices.
Partner with infrastructure and platform teams to optimize performance reliability scalability and cost management across enterprise data platforms.
Data Products & Information Architecture
Define enterprise standards for data products data contracts metadata management discoverability interoperability and lifecycle management.
Drive implementation of Data Mesh and federated data ownership principles across Abbott business domains.
Establish architecture patterns that enable reusable trusted and scalable data assets.
Partner with business and technology leaders to translate strategic priorities into scalable enterprise information architectures.
AI & Advanced Analytics Architecture
Architect AI-ready data ecosystems supporting machine learning predictive analytics Generative AI agentic AI and advanced analytics workloads.
Design reference architectures for Retrieval-Augmented Generation (RAG) semantic search vector databases knowledge repositories and enterprise AI platforms.
Define enterprise approaches for embeddings vector storage semantic retrieval knowledge management and AI-ready data foundations.
Establish LLMOps and MLOps standards for model deployment monitoring observability governance and lifecycle management.
Define architectural standards for feature stores training datasets metadata lineage and model operationalization.
Evaluate emerging AI technologies and translate them into practical enterprise adoption roadmaps.
Lead AI architecture assessments and provide technical recommendations for strategic AI investments.
Data Governance & Trust by Design
Partner with Data Governance and Information Management teams to ensure architectural alignment with metadata lineage master data data quality privacy security and regulatory requirements.
Define architectural controls that enable trusted auditable and governed enterprise data.
Promote trust by design principles throughout Abbotts data and AI ecosystem.
Required Qualifications
Masters degree in Computer Science Data Science Engineering Information Systems or a related field.
10 years of experience in enterprise data architecture cloud data platform architecture or large-scale analytics architecture.
5 years designing and implementing modern cloud-native data platforms and implementing enterprise-scale technology architectures and solutions.
Minimum 10 years of overall professional experience in technology with a strong background in enterprise architecture and solution design.
Minimum 3 years at the Director level or in a comparable senior individual contributor leadership role.
Demonstrated expertise in technical architecture leadership including establishing architectural direction and driving strategic technology initiatives.
Deep hands-on expertise with Snowflake Databricks Microsoft Fabric Azure Data Services or equivalent modern data platforms.
Proven experience designing and implementing large-scale lakehouse architectures.
Proven experience architecting AI-ready data ecosystems supporting machine learning Generative AI vector retrieval semantic search and RAG architectures.
Deep understanding of Data Mesh Data Fabric Data Products domain-driven design and modern information architecture principles.
Experience with enterprise integration patterns APIs event-driven architectures Kafka streaming platforms and real-time data processing.
Experience defining data architecture standards covering metadata lineage master data management and data quality.
Experience leading architecture reviews and providing technical oversight for strategic enterprise initiatives.
Strong communication skills with demonstrated ability to influence senior executives architects engineers and business stakeholders.
Preferred Qualifications
Experience serving as a Chief Data Architect Lead Data Architect Enterprise Data Architect Principal Architect or similar senior architecture leadership role.
Experience within healthcare medical devices life sciences pharmaceuticals or regulated manufacturing environments.
Hands-on expertise with Databricks Snowflake Microsoft Fabric Azure Kubernetes Apache Airflow Delta Lake Apache Iceberg Kafka and related cloud-native technologies.
Experience with vector databases knowledge graphs semantic search platforms and enterprise AI platforms.
Relevant certifications in Cloud Architecture Data Engineering AI Engineering Enterprise Architecture or related disciplines.
What Success Looks Like - Within the first 12 months this leader will:
Establish Abbotts target-state enterprise Data & AI Architecture and modernization roadmap.
Define enterprise standards for data products lakehouse architecture AI-ready datasets integration and platform design.
Accelerate modernization of legacy data environments while maintaining operational stability.
Increase adoption of reusable trusted and scalable enterprise data assets.
Enable scalable AI analytics and automation capabilities that directly support business outcomes.
Improve interoperability architectural consistency data quality and platform performance across Abbotts global ecosystem.
Be recognized by engineering and architecture teams as Abbotts technical authority for enterprise data architecture and AI-ready platforms.
The base pay for this position is
$149300.00 $298700.00In specific locations the pay range may vary from the range posted.
Abbott is an Equal Opportunity Employer of Minorities/Women/Individuals with Disabilities/Protected Veterans.
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About Company
WHO WE ARE CREATING LIFE-CHANGING TECHNOLOGY From removing the regular pain of fingersticks as people manage their diabetes to connecting patients to doctors with real-time information monitoring their hearts, from easing chronic pain and movement disorders to testing half the world’s ... View more
