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Data Engineer - Research Informatics

Job in City of Yonkers, Yonkers, Westchester County, New York, 10701, USA
Listing for: 2000 Montefiore Health System, Inc.
Full Time position
Listed on 2026-10-22
Job specializations:
  • IT/Tech
    Data Engineering, Information Security & Data Protection, Information & Knowledge Management, Data Analyst
Salary/Wage Range or Industry Benchmark: 128000 - 160000 USD Yearly USD 128000.00 160000.00 YEAR
Job Description & How to Apply Below

City/State:
Yonkers, New York

Grant Funded:
No

Department: IT
- Data & Analytics

Health Research Informatics

Work Shift:

Day

Work Days: MON-FRI

Scheduled

Hours:

8:30 AM-5 PM

Scheduled Daily

Hours:

7.5 HOURS

Pay Range: $-$

Montefiore Medical Center is nationally recognized for clinical excellence—breaking new ground in research, training the next generation of healthcare leaders, and delivering science-driven, patient-centered care. Montefiore is ranked among the top hospitals nationally and regionally by U.S. News & World Report. For more than 100 years, we have been innovating new treatments, procedures, and approaches to patient care, producing stellar outcomes, and raising the bar for medical centers in the region and worldwide.

As we build on this momentum, we continue to advance the practice of medicine and set the standard for excellence. Our workforce is among the most diverse in the US:
Montefiore associates speak 60+ languages.

Position Summary:

The Data Engineer, Research Informatics plays a critical role in enabling data-driven clinical and translational research across Montefiore. This position is responsible for designing, building, and maintaining scalable data pipelines and research-ready datasets that integrate complex, multi-source healthcare and research data, including EHR systems, clinical registries, and external datasets. Working at the intersection of clinical care and scientific discovery, the Data Engineer develops robust data models and infrastructure to support key research use cases such as cohort identification, longitudinal patient tracking, clinical trials, and real-world evidence generation.

This role emphasizes data quality, reproducibility, and compliance with regulatory standards, ensuring that data assets are reliable, secure, and suitable for research use. The Data Engineer will work closely with clinical researchers, biostatisticians, data scientists, and cross-functional teams to translate complex research and clinical questions into scalable data solutions. In addition, this role will collaborate side by side with data engineers across the broader Montefiore data organization, aligning with enterprise data standards, platforms, and best practices to ensure consistency, scalability, and interoperability across clinical, operational, and research domains.

This role also contributes to the advancement of enterprise research data platforms, supporting secure data access, governance, and innovation in analytics to improve patient outcomes and accelerate scientific discovery.

Responsibilities:
  • Develop and maintain research data pipelines that integrate clinical records, text, imaging, and other approved data sources.
  • Document data definitions, quality checks, metadata, lineage, and transformations to support FAIR aligned reuse.
  • Help implement standardized, governed data access workflows and reusable tools for cohort discovery, phenotyping, trial feasibility, recruitment planning, and research analytics.
  • Translate investigator needs into scoped requirements and track delivery.
  • Develop, benchmark, and validate AI methods, including information extraction, multimodal models, large or vision language models, and interpretable or knowledge informed approaches when suitable for the use case.
  • Turn validated methods into maintainable research services and interfaces, with version control, automated tests, monitoring, user documentation, and clear handoff to authorized operational partners.
  • Set evaluation plans with investigators and clinical experts, including baselines, validation splits, human review, error analysis, reproducibility checks, and assessment of subgroup performance and potential bias.
  • Work with ICTR, the Data Science Institute, and Montefiore data, IT, security,…
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