14 days ago
Base Salary
$149k - $299k/yr
Responsibilities
- Lead architecture reviews and provide final recommendations for major enterprise data, analytics, and AI initiatives.
- Define reference architectures and implementation standards for Snowflake, Databricks, Microsoft Fabric, Azure Data Services, lakehouses, data products, and AI platforms.
- Establish standards for data ingestion, transformation, orchestration, observability, DataOps, CI/CD, Infrastructure as Code, platform engineering, containerization, and automated deployment.
- Design enterprise information architectures covering canonical data models, domain ownership, metadata, lineage, data quality, interoperability, and lifecycle management.
- Guide Data Mesh, federated data ownership, enterprise integration, APIs, event-driven architectures, messaging, streaming, and real-time data processing.
- Architect AI-ready ecosystems supporting machine learning, predictive analytics, Generative AI, agentic AI, RAG, semantic search, vector retrieval, knowledge repositories, LLMOps, and MLOps.
- Partner with engineering, infrastructure, platform, governance, information management, business, and architecture teams to resolve complex technical challenges and optimize performance, reliability, scalability, and cost.
- Evaluate emerging technologies, define modernization roadmaps, and influence strategic enterprise technology decisions as Abbott’s technical authority for data and AI architecture.
Requirements
- Master’s 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 enterprise-scale technology architectures and solutions.
- 10+ years of overall professional technology experience with a strong background in enterprise architecture and solution design.
- At least 3 years at the Director level or in a comparable senior individual contributor leadership role.
- Demonstrated technical architecture leadership, including setting 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 large-scale lakehouse architectures and AI-ready data ecosystems supporting machine learning, Generative AI, vector retrieval, semantic search, and RAG.
- Strong understanding of Data Mesh, Data Fabric, Data Products, domain-driven design, modern information architecture, metadata, lineage, master data management, and data quality.
- Experience with enterprise integration patterns, APIs, event-driven architectures, Kafka, streaming platforms, and real-time data processing.
- Experience leading architecture reviews and providing technical oversight for strategic enterprise initiatives.
- Strong communication skills and the ability to influence executives, architects, engineers, and business stakeholders.
- Preferred experience as a Chief Data Architect, Lead Data Architect, Enterprise Data Architect, Principal Architect, or similar senior architecture leader.
- Preferred experience in healthcare, medical devices, life sciences, pharmaceuticals, or regulated manufacturing, along with relevant cloud, data engineering, AI engineering, or enterprise architecture certifications.
Tech Stack
Categories
Data Engineering
About Abbott
Abbott is a NYSE‑listed healthcare company that develops diagnostics, medical devices, nutrition products, and branded generic medicines for clinicians and consumers. Founded in 1888 and headquartered in Abbott Park, Illinois, it sells products in more than 160 countries, including the FreeStyle Libre continuous glucose monitoring system. Revenue comes primarily from product sales to hospitals, clinics, and retail channels.