Healthcare Data Engineer – Research Informatics

Montefiore Health System; Plaza (ND); On-site; USD 128,000 - 160,000; Full time

Job summary

Montefiore Health System in Yonkers, NY seeks a Data Engineer in Research Informatics to design, build, and maintain scalable data pipelines. You will integrate complex healthcare data sources, including EHRs and registries, to support cohort identification, longitudinal tracking, and real-world evidence generation.

The role emphasizes data quality, reproducibility, and regulatory compliance, with close collaboration across researchers, biostatisticians, and data engineers to ensure scalable and

Qualifications

• Master’s degree or equivalent in AI, computer science, bioinformatics, or related field.
• Experience with medical imaging, NLP, large language or vision-language models, and multimodal learning.
• Experience with GPU/ HPC, reproducible model training, containers, SQL, APIs, or data platforms.
• Familiarity with FAIR data practices, ontologies, data provenance, and responsible AI.
• Proven research communication through publications, talks, or open source work.

Responsibilities

• Develop and maintain research data pipelines integrating clinical records, text, imaging and approved data sources.
• Implement governed data access workflows for cohort discovery, phenotyping, and trial feasibility.
• Develop and validate AI methods, including multimodal models and interpretable approaches.
• Turn methods into maintainable services with versioning, tests, and documentation.
• Collaborate with researchers, data scientists, and IT to align with enterprise data standards.

Skills

Clinical AI

NLP/Info extraction

Multimodal learning

Research data platforms

LLMs

Education

Master’s degree or equivalent

Tools

GPU HPC

SQL

APIs

Containers

Data pipelines

Job description

Montefiore Health System in Yonkers, NY seeks a Data Engineer in Research Informatics to design, build, and maintain scalable data pipelines. You will integrate complex healthcare data sources, including EHRs and registries, to support cohort identification, longitudinal tracking, and real-world evidence generation.

The role emphasizes data quality, reproducibility, and regulatory compliance, with close collaboration across researchers, biostatisticians, and data engineers to ensure scalable and