Principal Data Architect

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.

The Opportunity Abbott is seeking a highly skilled and strategic Lead Data & Solutions Architect to support the development, management, and modernization of the enterprise data ecosystem that powers our next-generation business capabilities. This role will lead the design and implementation of scalable cloud-based data platforms, architecture standards, governance frameworks, and data products that enable enterprise-wide AI, analytics, and data-driven decision making. The ideal candidate combines deep technical expertise in Databricks, AWS, Azure, modern data architectures, and data engineering practices with strong business acumen and leadership capabilities. Healthcare and EMR/EHR experience is highly desirable as Abbott continues to expand the use of clinical, operational, and commercial data assets to accelerate innovation and business outcomes.

Define and maintain enterprise-wide data architecture standards, principles, roadmaps, and governance frameworks. Lead the design and implementation of scalable cloud-native data platforms leveraging Databricks, AWS, Azure, and related technologies. Architect and oversee batch, streaming, and real-time data pipelines supporting analytics, AI, machine learning, and operational use cases. Partner with business, product, analytics, AI, and engineering teams to translate strategic objectives into scalable data solutions. Design and optimize Lakehouse architectures, enterprise data lakes, data warehouses, and data integration frameworks. Enable self-service data and analytics capabilities that improve accessibility, trust, and usability of enterprise data assets. Support enterprise AI initiatives by ensuring high-quality, governed, and scalable data foundations. Establish best practices for data modeling, metadata management, data lineage, master data management, and data quality. Drive automation of data workflows, orchestration processes, monitoring, and operational support to enable near real-time data access. Ensure data security, privacy, compliance, and governance across all platforms and data domains. Collaborate with cybersecurity, legal, and compliance teams to implement appropriate controls for sensitive and regulated data. Guide cloud strategy across AWS and Azure environments, ensuring scalability, reliability, cost optimization, and operational excellence. Mentor and provide technical leadership to data engineers, architects, and cross-functional technology teams. Conduct architecture reviews and technology assessments, identifying opportunities for modernization and innovation. Evaluate emerging technologies and industry trends to advance Abbott’s data, analytics, and AI capabilities. Support enterprise initiatives involving healthcare, EMR/EHR, clinical, operational, and commercial data when applicable.

Bachelor's degree in computer science, Information Systems, Engineering, Data Science, or a related technical discipline. 8+ years of experience in data architecture, solution architecture, data engineering, or related enterprise technology roles. 5+ years of experience designing and implementing enterprise-scale cloud data platforms. Deep hands-on experience with Databricks, including: Delta Lake Unity Catalog Databricks Workflows Databricks SQL Spark and PySpark Lakehouse Architecture Strong expertise with AWS services such as S3, Glue, IAM, Redshift, Lambda, Kinesis, and Lake Formation. Strong expertise with Microsoft Azure services such as Azure Data Lake Storage (ADLS), Azure Data Factory, Synapse, Azure Key Vault, and Microsoft Purview. Extensive