Senior Cloud Platform Engineer

Position Summary Senior Cloud Platform Engineer role to design, build, and operate secure cloud-based research data infrastructure for multi‑institution biomedical and translational research programs, supporting data ingestion, harmonization, metadata and provenance tracking, secure analytic workspaces, APIs, and federated data access. Job Responsibilities Design, build, and maintain secure, scalable cloud infrastructure for ingestion, storage, transformation, indexing, and governed access to 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. Minimum Qualifications Masters degree in a quantitative discipline (Biomedical Informatics, Computer Science, Machine Learning, Applied Statistics, Mathematics, or similar). 5-7 years of experience in machine learning/data science. Proficiency in at least one programming language (Python, R) and machine learning tools (scikit‑learn, R). Knowledge of predictive modeling and machine learning concepts, including design, development, evaluation, deployment, and scaling to large datasets. Familiarity with big data computing models (Hadoop/MapReduce, Spark, etc.). Knowledge of databases (Relational/SQL, NoSQL such as MongoDB). Preferred Qualifications 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. Knowledge of metadata management, provenance, lineage, validation, and operational quality assurance for data‑intensive systems. 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. Experience with biomedical data models, semantic technologies, provenance standards, 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. Benefits Comprehensive benefits and wellness package, including financial security benefits, generous time‑off program, employee resource groups, and a holistic wellness program covering physical, mental, nutritional, sleep, social, financial, and preventive care. EEO Statement NYU Grossman School of Medicine is an equal‑opportunity employer and is committed to inclusion. All qualified individuals are encouraged to apply and will receive consideration. Salary Range $121,792.22 – $162,052.80 annually. #J-18808-Ljbffr NYU Grossman School of Medicine