Principal Architect - Research Data

Brown Medicine

2d•$134,035 - $221,187•Onsite

About The Position

Reporting to the Vice President and Chief Data Analytics Officer, the Principal Architect – Research Data leads the architecture, design, and technical implementation of Brown University Health’s research data ecosystem. The role is responsible for helping build a modern, scalable, secure, and governed data environment that enables researchers to discover, access, integrate, and analyze clinical and biomedical data. This senior, hands-on technical architecture role provides leadership across cloud-based research data platforms, including enterprise research data repositories, common data models, structured and unstructured clinical data, data integration, and capabilities for advanced analytics, artificial intelligence, and machine learning. The Principal Architect defines architecture and technical direction while working directly with engineering teams to design and implement critical components. The position collaborates with researchers, clinicians, Data & Analytics, Information Services, research administration, security, privacy, and other stakeholders to translate research needs into scalable, reusable, and sustainable enterprise data capabilities. It reports to the Vice President and Chief Data Analytics Officer and has no direct supervisory responsibility.

Requirements

Bachelor’s degree in Computer Science, Data Engineering, Computer Engineering, Biomedical Informatics, Health Informatics, Information Systems, or a related technical field; equivalent combinations of education and relevant professional experience may be considered.
At least 15 years of progressively responsible experience in data architecture, data engineering, software engineering, healthcare informatics, or related technology disciplines, including significant experience designing and leading complex data platform initiatives.
Senior-level experience architecting and delivering complex data platforms, preferably in a large healthcare, academic medical center, life sciences, or biomedical research environment.
Deep expertise in modern data architecture, data engineering, data modeling, data integration, and designing and implementing large-scale clinical or research data platforms.
Demonstrated experience architecting or engineering data platforms that support clinical or biomedical research.
Experience with i2b2, OMOP, or similar clinical research common data models and research data architectures.
Strong understanding of healthcare and biomedical data, including electronic health record data and the complexities of using clinical data for research and analytics.
Hands-on software or data engineering experience developing production data platforms, pipelines, services, applications, or other data capabilities.
Experience translating complex researcher and stakeholder needs into scalable technical architectures and reusable enterprise capabilities.
Ability to evaluate technologies, develop architectural recommendations, and move from architecture and design through hands-on implementation.
Strong analytical and problem-solving skills and the ability to navigate complex technical and organizational environments.
Excellent communication and collaboration skills, including the ability to engage effectively with researchers, clinicians, technical teams, operational leaders, and senior stakeholders.
Ability to provide technical leadership and work effectively across organizational and disciplinary boundaries.

Nice To Haves

Master’s degree in Computer Science, Biomedical Informatics, Data Science, Engineering, or a related field.
Experience designing and implementing solutions using modern cloud data platforms and services, including Microsoft Azure, Snowflake, Databricks, or comparable technologies.
Experience designing or implementing batch and real-time healthcare data integration, including familiarity with interoperability standards and technologies such as HL7 and FHIR.
Programming experience in Python; experience with C#, Java, C++, or other object-oriented programming languages is also desirable.
Experience with structured and unstructured healthcare data, including clinical notes, reports, documents, and other narrative clinical information.
Experience architecting, developing, or enabling data platforms for artificial intelligence, machine learning, clinical natural language processing, or related advanced analytic applications.
Familiarity with large language models or other advanced natural language processing approaches for extracting, classifying, summarizing, or otherwise analyzing clinical and biomedical text.
Experience designing healthcare data solutions within privacy, security, governance, data-quality, and access-control requirements.

Responsibilities

Define and lead the technical architecture and roadmap for the enterprise research data ecosystem, including secure, scalable, interoperable cloud-based platforms integrating clinical, biomedical, operational, and other research data.
Architect reusable research data capabilities for cohort discovery, feasibility analysis, data extraction, retrospective and observational research, real-world data analyses, and other research use cases, using models such as i2b2, OMOP, or comparable approaches.
Provide hands-on technical leadership in designing and developing data platforms, pipelines, transformations, services, applications, and data products for the research environment.
Architect scalable capabilities to ingest, integrate, organize, and make available structured and unstructured clinical data, including clinical notes and other narrative information, for advanced analytics, AI, machine learning, and natural language processing.
Design integration approaches across enterprise source systems, including batch and, where appropriate, real-time data flows and healthcare interoperability technologies.
Translate researcher, clinician, and stakeholder needs into scalable technical architectures and reusable data capabilities, coordinating with Information Services and other technology teams to align solutions with enterprise infrastructure, security, identity, and operational requirements.
Partner with data governance, privacy, security, compliance, and research leadership to ensure solutions meet requirements for data access, privacy, security, provenance, quality, and responsible data use.
Evaluate emerging technologies and architectural approaches relevant to research data, healthcare interoperability, advanced analytics, AI, and clinical informatics, and incorporate appropriate technologies into the ecosystem.
Provide technical direction to engineers, developers, analysts, and other contributors, and maintain architectural and technical documentation for platforms, data flows, integration patterns, and design decisions.
Perform other duties as assigned.