Data Architect

The Position

The Lead Data Architect for Clinical Imaging and AI Platforms will lead the design, governance, and evolution of enterprise imaging and multi-modal data ecosystems. This role serves as the strategic bridge between scientific, business, and technology organizations, translating business priorities into scalable, secure, and interoperable data architectures while ensuring alignment with GxP, SaMD, and FAIR frameworks.

Job Responsibilities

• Define and execute the enterprise data architecture strategy and roadmap for multi-modal imaging and research data.
• Design scalable and interoperable data architectures supporting Radiology, Digital Pathology, AI/ML, clinical, and translational research workflows.
• Establish and enforce standards for data modeling, metadata management, lineage, interoperability, and governance.
• Lead the design and implementation of cloud-native data platforms, data lakes, and distributed analytics ecosystems.
• Partner with stakeholders to translate business and research requirements into scalable, compliant, and reusable data solutions.
• Ensure alignment with GxP, FAIR, HIPAA/GDPR, and enterprise governance standards.
• Drive adoption of common data models, APIs, and semantic frameworks to improve data accessibility.
• Collaborate with engineering teams to design robust data ingestion, transformation, and storage patterns optimized for AI/ML.
• Define architecture patterns for high-volume imaging data, including metadata indexing and federated access strategies.
• Lead modernization efforts for legacy data environments and drive automation across data lifecycle management.
• Oversee architecture reviews and cross-functional design decisions to ensure operational excellence.
• Monitor emerging technologies in imaging data formats, AI/ML, and digital pathology to guide innovation.
• Drive the evolution of AI-ready data architectures supporting generative AI use cases.
• Foster a culture of technical excellence and knowledge sharing within the global data community.

Qualifications

• 8-10 years of industry experience in relevant fields with supporting education in Technology.
• Demonstrated experience defining technical direction and driving large-scale enterprise data initiatives.
• Proven track record in enterprise architecture strategy within regulated or highly governed environments.
• Deep expertise in distributed data systems, cloud-native platforms, and scalable analytics ecosystems.
• Strong experience with technologies such as Snowflake, Databricks, AWS, Azure, or GCP.
• Expertise in data modeling, metadata management, and enterprise data governance frameworks.
• Understanding of healthcare interoperability standards such as DICOM, HL7/FHIR, OMOP, CDISC, and SDTM.
• Experience architecting AI/ML-ready data environments and processing large-scale structured and unstructured datasets.
• Proficiency in Infrastructure as Code (IaC), CI/CD pipelines, and automated deployment patterns.
• Strong background in security architecture, privacy controls, and regulatory compliance.
• Excellent coaching, mentorship, and stakeholder management skills.