WHDH Data Solutions Architect

Universities of Wisconsin • Madison, WI

1d • $110,000 • Remote

About The Position

The Wisconsin Health Data Hub (WHDH), funded by the U.S. Economic Development Administration (EDA), is developing a secure, cloud-native data platform designed to deliver high-quality real-world data to support biomedical research, advanced analytics, and AI-driven discovery. The Data Solutions Architect provides senior technical leadership responsible for designing, implementing, and governing the architecture of WHDH’s data platform. This role ensures the secure, scalable integration, storage, and analysis of complex clinical and research data assets across a cloud-based environment. The position supports advanced analytics, machine learning, and federated research capabilities while maintaining compliance with HIPAA and institutional data governance standards. Working closely with data engineers, AI specialists, security analyst, and governance leaders, the Data Solutions Architect will translate research and operational requirements into scalable data architecture solutions that support WHDH’s long-term platform strategy.

Requirements

• At least 3 years' experience designing and implementing enterprise-scale data architectures; 5 years' preferred
• Expertise with cloud-native data platforms and distributed data solutions.
• Experience designing secure data pipelines and large-scale data integration frameworks.
• Familiarity with healthcare or biomedical research data environments and relevant regulatory requirements.
• Bachelor's degree preferred; focus in Computer Science, Information Systems, Data Engineering, or related field preferred.

Nice To Haves

• Experience with healthcare data standards and interoperability frameworks.
• Experience supporting AI/ML and advanced analytics workloads.
• Expertise with federated data architectures and secure multi-institutional data collaboration.
• Experience working in federally funded research programs or academic research environments.
• Strong documentation and technical leadership skills

Responsibilities

• Data Architecture and Platform Design: Design and implement the architectural framework supporting WHDH’s secure, cloud-native data platform. Develop scalable architectures for ingesting, harmonizing, storing, and delivering structured and unstructured health data. Establish data models, metadata frameworks, and integration architectures that support advanced research workflows. Design high-performance analytics capabilities enabling AI, machine learning, and large-scale data analysis.
• Data Integration and Interoperability: Architect secure data pipelines for ingestion and transformation of multi-source clinical and research datasets. Enable interoperable data exchange across contributing health systems and research institutions. Implement scalable services supporting federated queries, distributed analytics, and secure data sharing.
• Data Governance and Security: Ensure compliance with HIPAA, institutional governance policies, and research data security standards. Establish architectural best practices related to data governance, reproducibility, and responsible use of sensitive health data. Design solutions that support secure access control, auditing, and governance across the WHDH data ecosystem.
• Platform Innovation and Strategy: Guide the adoption of modern data platform architecture that enhance data discovery, metadata management, and scalable research workflows. Evaluate and implement emerging trends that improve interoperability, accessibility, and performance of WHDH data assets. Develop modular, extensible platform components that enable technology transfer and sustainability beyond the grant period.
• Collaboration and Leadership: Collaborate with cross-functional teams including data engineers, AI researchers, security analyst, and governance leaders. Provide leadership in defining system design patterns and platform architecture standards. Support multi-institutional research initiatives by enabling secure and scalable collaborative data environments.
• Develops architectural patterns that support large-scale biomedical datasets, including real-world data, clinical text, imaging, and genomic data, enabling advanced analytics, machine learning, and AI-driven research workflows within a secure cloud environment
• Designs and implements data architecture that enables secure ingestion, normalization, and integration of clinical, research, and operational data from multiple health system partners while ensuring compliance with HIPAA, institutional policies, and data use agreements
• Participates in the evaluation of vendor software releases, upgrade planning, and impact. Documents and communicates system enhancements or changes
• Integrates, identifies, troubleshoots, monitors, and resolves complex and varied supported services, systems, network, and application problems according to established processes and procedures
• Assists in the design of system and infrastructure specifications, implementation, and/or integration, trend analysis, and capacity planning
• Designs small components and runs, maintains, and operates technical systems and infrastructure
• Plans, coordinates, and executes the development, testing, implementation, integration, and installation of moderately complex system resources, upgrades, and security components in alignment with industry best practices
• Defines and implements standards for healthcare data interoperability using frameworks such as HL7 FHIR, OMOP Common Data Model, and other biomedical data models to ensure consistent, high-quality data exchange across contributing institutions and research partners
• Serves as an expert point of contact for external stakeholders and IT partners regarding system integrations, identifies needs, provides solution options, and communicates issue updates and resolutions
• Plans and directs staff implementation of small to medium technical projects as needed
• Architects systems that enable privacy-preserving analytics, federated queries, and secure multi-institutional collaboration while maintaining strict data governance controls and enabling authorized researchers to discover and analyze distributed health datasets

Benefits

• generous vacation, holidays, and sick leave
• competitive insurances and savings accounts
• retirement benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level