Data Engineer II - Surgery

The Mount Sinai Program for Surgical Intelligence is seeking a Data Engineer to support the development and deployment of data-driven tools in surgical care. This role will focus on building and maintaining data pipelines, managing surgical datasets (including operative video), and supporting execution of technical and clinical research initiatives.

The Data Engineer will work closely with surgeons, engineers, and researchers to ensure surgical data is reliable, well-organized, and accessible for downstream analytics and machine learning applications. This is a hands-on role with significant responsibility and opportunities for growth. Prior experience working with healthcare data systems is strongly preferred, as this role will require immediate engagement with clinical datasets and interoperability challenges.

The role may be hybrid but will be partially on-site at the Mount Sinai Hospital campus on the Upper East Side of Manhattan. The position will be managed by surgeons within the Mount Sinai Department of Surgery who will serve as clinical experts and liaisons for real world application of the work, as well as information technology experts who will provide the appropriate technical resources to carry out the role successfully.


 

• Design, build, and maintain data pipelines for surgical datasets, including structured data and operative video
• Support ingestion, organization, curation, and access control for an operative video repository
• Collaborate with clinical and research teams to define data schemas, metadata standards, and labeling conventions
• Ensure data quality, traceability, and reproducibility across projects
• Build durable data pipelines and organizational structures that support ongoing research and clinical deployment, rather than one-off analyses
• Support execution of research and clinical AI projects across the Department of Surgery
• Track project milestones, deliverables, and documentation
• Maintain datasets, technical documentation, and shared resources
• Coordinate with engineers, clinicians, and institutional partners to ensure smooth project execution
• Engage with surgical teams to understand clinical workflows and data generation processes
• Translate clinical needs into technical requirements and actionable tasks
• Identify and resolve data-related bottlenecks affecting research and deployment efforts
   

• Bachelors degree in Computer Science or a related discipline; Advanced degree preferred.
• 4+ years relevant professional development experience, preferably in a LINUX environment.
• Strong SQL and NoSQL Database Knowledge: Oracle, PostgreSQL/MYSQL, and Mongo DB (or similar).
• Proficiency with at least 2 programming languages among Scala/Python/ Java. Must be flexible and fast to pick up new languages.
• Proficiency in Restful service development, preferably with Node JS, Django and PHP.
• Experience with micro-services and SOA.
• Proficiency on installation and configuration of big data software and technology
• Knowledge of Hadoop, Spark, Kafka and other big data technology stacks and streaming tools.
• Familiarity with and the ability to leverage a wide variety of open source technologies and tools.
• Working knowledge of cloud architecture and implementation onAzure or AWS, is a big plus. Experience with serverless computing, creating VMs, cloud security, and other cloud services is also a big plus.
• Experience working in an Agile methodology. Experience working with JIRA is a plus.
• Strong organizational skills and ability to manage work in an evolving environment
• Effective communication skills with both technical and non-technical stakeholders
• Prior experience working with healthcare data, including electronic health record (EHR) systems, clinical registries, or medical imaging datasets preferred.
• Familiarity with healthcare data models and standards (such as Epic Clarity, Caboodle, OMOP, FHIR, HL7) and clinical coding systems (e.g., ICD-10, CPT, LOINC, RxNorm) preferred.
• Experience handling regulated data environments, including HIPAA-compliant workflows and data governance practices preferred.
• Experience with data integration across heterogeneous sources (e.g., EHR + imaging + research datasets) preferred.
• Experience with video data or large unstructured datasets preferred.
• Interest in building repeatable, well-documented data pipelines that support ongoing research and clinical deployment preferred.

Non-Bargaining Unit, 862 - Surgery - ISM, Icahn School of Medicine