Senior Cloud Platform Engineer

We have an exciting opportunity to join our team as a Senior Data Science Analyst/Engineer.

The Senior Cloud Platform Engineer to design, build, and operate secure cloud-based research data infrastructure for multi-institution biomedical and translational research programs.

This role will support data ingestion, harmonization, metadata and provenance tracking, secure analytic workspaces, APIs, and federated data access. The engineer will work closely with data scientists, informaticians, domain researchers, security and compliance teams, and enterprise engineering groups.

The ideal candidate is a hands-on platform engineer with experience building data-intensive cloud systems and supporting controlled-access research or regulated data environments. Experience with trusted research environments, secure enclaves, scientific data platforms, or federated analytics is especially relevant., * Design, build, and maintain secure, scalable cloud infrastructure for ingestion, storage, transformation, indexing, and governed access to heterogeneous research data.

• Develop cloud-native and cloud-portable services, initially in AWS or comparable environments, using automation, observability, and reproducible deployment practices.
• Build and support data pipelines that transform heterogeneous source data into metadata-rich, analysis-ready assets using agreed schemas, ontologies, provenance frameworks, and quality-control checks.
• Implement and maintain trusted research environments and secure analytic workspaces, including provisioning, access control, auditing, lifecycle management, and project-scoped environments.
• Develop APIs and platform services for data discovery, retrieval, interoperability, metadata search, and federated query across institutional nodes.
• Integrate harmonization, curation, metadata, ontology, and quality-assurance components developed by domain and informatics teams into production workflows.
• Implement software quality practices, including automated testing, CI/CD, infrastructure-as-code, monitoring, incident response, release documentation, and technical documentation.
• Collaborate with engineers, informaticians, data stewards, analysts, investigators, and governance stakeholders to translate program requirements into durable technical solutions.
• Communicate architecture decisions, progress, risks, dependencies, and technical tradeoffs clearly to technical and non-technical stakeholders.

To qualify you must have a Masters degree in a quantitative discipline (Biomedical Informatics, Computer Science, Machine Learning, Applied Stascs, Mathematics or similar field) and 5-7 years of experience in machine learning/ data science. Proficiency in at least one programming language (Python, R) and machine learning tools (scikitlearn, R) Knowledge of predictive modeling and machine learning concepts, including design, development, evaluation, deployment and scaling to large datasets Familiarity with computing models for big data Hadoop / MapReduce, Spark etc. Knowledge of databases (Relational / SQL, NOSQL MongoDB etc.), Technical skills Strong software engineering skills in Python, Java, or comparable languages used for platform or service development. Strong proficiency with SQL, data pipeline design, and structured or semi-structured data processing. Experience with AWS, Azure, or Google Cloud, including storage, compute, networking, identity and access management, and deployment services. Experience with containers, version control, CI/CD, infrastructure-as-code, and automated testing. Experience designing or integrating APIs and service-oriented architectures for interoperable data systems. Working knowledge of metadata management, provenance, lineage, validation, and operational quality assurance for data-intensive systems. Preferred qualifications Experience with cloud-based research environments, secure data enclaves, virtual research workspaces, or controlled-access scientific computing platforms. Experience with federated analytics, federated query, distributed data architectures, or multi-node interoperability patterns. Familiarity with biomedical or translational research data, FAIR-aligned data management, metadata standards, ontology-aware systems, or research data harmonization practices. Experience with biomedical data models, semantic technologies, provenance standards, or ontology-enabled data integration. Experience supporting collaborative research programs that combine data, code, models, documentation, and governed computational environments. Familiarity with AI-enabled engineering tools for code generation, code review, testing, and documentation within disciplined production workflows.

Qualified candidates must be able to effectively communicate with all levels of the organization.

NYU Grossman School of Medicine provides its staff with far more than just a place to work. Rather, we are an institution you can be proud of, an institution where you'll feel good about devoting your time and your talents. At NYU Langone Health, we are committed to supporting our workforce and their loved ones with a comprehensive benefits and wellness package. Our offerings provide a robust support system for any stage of life, whether it's developing your career, starting a family, or saving for retirement. The support employees receive goes beyond a standard benefit offering, where employees have access to financial security benefits, a generous time-off program and employee resources groups for peer support. Additionally, all employees have access to our holistic employee wellness program, which focuses on seven key areas of well-being: physical, mental, nutritional, sleep, social, financial, and preventive care. The benefits and wellness package is designed to allow you to focus on what truly matters. Join us and experience the extensive resources and services designed to enhance your overall quality of life for you and your family.

NYU Grossman School of Medicine is an equal opportunity employer and committed to inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration. We require applications to be completed online.

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NYU Langone Health provides a salary range to comply with the New York state Law on Salary Transparency in Job Advertisements. The salary range for the role is $121,792.22 - $162,052.80 Annually. Actual salaries depend on a variety of factors, including experience, specialty, education, and hospital need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.

NYU Grossman School of Medicine is one of the nation's top-ranked medical schools. For 175 years, NYU Grossman School of Medicine has trained thousands of physicians and scientists who have helped to shape the course of medical history and enrich the lives of countless people. An integral part of NYU Langone Health, the Grossman School of Medicine at its core is committed to improving the human condition through medical education, scientific research, and direct patient care. At NYU Langone Health, equity and inclusion are fundamental values. We strive to be a place where our exceptionally talented faculty, staff, and students of all identities can thrive. We embrace inclusion and individual skills, ideas, and knowledge.