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Brown University Health

Remote behavioral health care platform analytics

Principal Architect - Research Data

Data EngineeringPosted on Nov 13
Full-timeRemote in USA$134k - $221.2k

About the Job

Requirements

  • A bachelor's degree in Computer Science, Data Engineering, Computer Engineering, Biomedical Informatics, Health Informatics, Information Systems, or a related technical field is required; 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 data platforms, pipelines, services, applications, or other production 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 progress from architecture and design through hands-on implementation.
  • Ability to navigate complex technical and organizational environments using analytical and problem-solving skills.
  • 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.

Responsibilities

  • Define and lead the technical architecture and roadmap for the enterprise research data ecosystem, including scalable, secure, and interoperable cloud-based platforms integrating clinical, biomedical, operational, and other research data.
  • Architect reusable research data capabilities supporting cohort discovery, feasibility analysis, data extraction, retrospective and observational research, real-world data analyses, and other research uses, including established 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, enabling advanced analytics, artificial intelligence, 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, collaborating with Information Services and technology teams to align research solutions with enterprise infrastructure, security, identity, and operational requirements.
  • Partner with data governance, privacy, security, compliance, and research leadership to ensure research data 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, artificial intelligence, and clinical informatics, and incorporate appropriate technologies into the research data ecosystem.
  • Provide technical direction to engineers, developers, analysts, and other contributors, and maintain architectural and technical documentation for key platforms, data flows, integration patterns, and design decisions.
  • Perform other duties as assigned.

Desired Qualifications

  • A master's degree in Computer Science, Biomedical Informatics, Data Science, Engineering, or a related field is preferred.
  • 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 Health Level Seven and Fast Healthcare Interoperability Resources.
  • Programming experience in Python; experience with C#, Java, C++, or other object-oriented programming languages is also desirable.
  • Experience working with structured and unstructured healthcare data, including clinical notes, reports, documents, and other narrative clinical information.
  • Experience architecting, developing, or enabling data platforms supporting artificial intelligence, machine learning, clinical natural language processing, or related advanced analytic applications.
  • Familiarity with using large language models or other advanced natural language processing approaches to extract, classify, summarize, or otherwise analyze clinical and biomedical text.
  • Experience designing healthcare data solutions within privacy, security, governance, data-quality, and access-control requirements.

About the Company

Brown University Health

Remote behavioral health care platform analytics

Memoir Health built a behavioral healthcare platform for home-based care, helping healthcare organizations manage patients remotely. The platform includes remote patient monitoring, scheduling, virtual care, and outcomes management, powered by a data analytics engine that highlights cost-saving opportunities and guides proactive care. It stands out by automating care journeys and delivering integrated, outcomes-focused care within managed care networks, reducing administrative work for clinicians. Its goal is to make care more proactive, accessible, and coordinated from home, aiming to improve patient outcomes while lowering costs; Memoir Health was acquired by Lumeo Health in 2020.

Company size
1-10
Company stage
Seed
Total funding
$7.5M
Headquarters
New York City, New York
Founded
2018

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