Data Engineer, Research Informatics

Montefiore Health System; City of Yonkers (NY); On-site; USD 128,000 - 160,000; Full time

Job summary

Montefiore Health System in Yonkers, NY seeks a Data Engineer for Research Informatics to design, build, and maintain scalable data pipelines and research-ready datasets spanning EHRs, registries, and external sources.

Working at the intersection of clinical care and discovery, you will develop robust data models, ensure data quality, and support cohort identification, trials, and real-world evidence generation, collaborating with researchers, biostatisticians, and data scientists to deliver

Qualifications

• Master’s degree or equivalent in AI, CS, Biomed informatics, or related field.
• Experience with medical imaging, NLP, LLMs, multimodal learning, or sensitive health data.
• Experience with GPU/ HPC, reproducible training, containers, SQL, APIs, or research data platforms.
• Familiarity with FAIR data practices, ontologies, data provenance, and responsible AI.

Responsibilities

• Develop and maintain data pipelines integrating clinical records, text, imaging, and approved sources.
• Implement governed data access workflows for cohort discovery, phenotyping, and trials.
• Develop, benchmark, and validate AI methods for research use cases.
• Turn methods into maintainable research services with docs and tests.
• Set evaluation plans with investigators, including baselines and bias checks.
• Collaborate with ICTR, Data Science Institute, and Montefiore teams on governance.
• Support investigators with training, demonstrations, and reusable examples.
• Track service measures and report progress and issues.

Skills

Data engineering

AI/ML knowledge

Clinical research familiarity

Education

Master’s degree

Tools

SQL

APIs

Containers

GPU computing

High-performance computing

Job description

Montefiore Health System in Yonkers, NY seeks a Data Engineer for Research Informatics to design, build, and maintain scalable data pipelines and research-ready datasets spanning EHRs, registries, and external sources.

Working at the intersection of clinical care and discovery, you will develop robust data models, ensure data quality, and support cohort identification, trials, and real-world evidence generation, collaborating with researchers, biostatisticians, and data scientists to deliver