Data Architect — Roche

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At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters. The Position The Lead Data Architect – Clinical Imaging and AI Platforms will lead the design, governance, and evolution of enterprise imaging and multi-modal data ecosystems, ensuring alignment with GxP, SaMD, FAIR, and clinical data governance frameworks. This role serves as the strategic bridge between scientific, business, and technology organizations across Research, Product Development, RIS, and RDT, translating business priorities into scalable, secure, and interoperable data architectures. The role is responsible for defining enterprise data architecture strategy and establishing standards for metadata, interoperability, lineage, and AI-ready data models. It will enable scalable analytics and AI/ML workflows for Research (REDs) and Product Development(PD) while driving modernization of imaging data platforms in partnership with engineering, informatics, and governance teams. Job Responsibilities

• Define and execute the enterprise data architecture strategy and roadmap for multi-modal imaging and research data within the Global Imaging Platform (GIP ).
• 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, cataloging, and governance across structured and unstructured datasets in close partnership with the Data managers and Study teams.
• Lead the design and implementation of cloud-native data platforms, data lakes/lakehouses, and distributed analytics ecosystems supporting global R&D and clinical initiatives.
• Partner with scientific, clinical, and technical stakeholders to translate business and research requirements into scalable, compliant, and reusable data solutions.
• Act as the primary architecture lead for imaging and multi-modal data ecosystems, coordinating across gRED, pRED, PD, RDT, RIS, and enterprise IT functions.
• Ensure alignment with GxP, FAIR standards, HIPAA/GDPR, security, privacy, and enterprise governance standards across all data architecture initiatives.
• Drive enterprise-wide adoption of common data models, interoperability standards, APIs, and semantic frameworks to improve data accessibility and reusability.
• Collaborate with engineering and platform teams to design robust data ingestion, transformation, storage, and access patterns optimized for AI/ML and advanced analytics, focussed on biomarker research and analysis of Imaging data.
• Define architecture patterns for high-volume imaging and pathology data, including metadata indexing, streaming, archival, and federated access strategies.
• Lead modernization efforts for legacy data environments towards scalable and efficient hybrid architectures.
• Drive automation and standardization across data lifecycle management, data quality monitoring, observability, and governance workflows.
• Oversee architecture reviews, technical governance, and cross-functional design decisions to ensure consistency, scalability, and operational excellence.
• Identify and implement opportunities to improve scalability, cost optimization, performance, automation, and operational efficiency across enterprise data platforms.
• Monitor emerging technologies and industry trends in data platforms, imaging data formats, AI/ML ecosystems, digital pathology, interoperability, and data standards to guide innovation and future-state architecture.
• Drive the evolution of AI-ready and semantically enriched