Data Engineer

The Data Engineer will play a key role in designing, building, and maintainig scalable data pipelines, curated analytical data models, and cloud-based data products that support enterprise supply chain analytics and operations.

• Data Engineer within healthcare
• Hands on with Python and SQL - Unable to sponsor candidates, * Design, build, and maintain scalable batch data pipelines, transformation workflows, dimensional models, and curated analytical data models using SQL, Python, Databricks, Apache Spark/PySpark, and distributed data processing technologies.
• Define and maintain source-to-target mappings and transformation logic for data integrated from enterprise platforms including Epic, Oracle, ParEx, GHX, PeopleSoft, and other supply chain systems.
• Implement automated data quality, reconciliation, validation, and testing processes to ensure reliable, production-ready datasets.
• Optimize data processing, query performance, compute utilization, and storage design across relational and distributed data platforms.
• Develop, test, deploy, monitor, and support data solutions across development and production environments, following established release management, change management, and deployment practices.
• Provide operational support for production data pipelines, including incident triage, root cause analysis, issue resolution, and recovery of failed workflows.
• Implement workflow orchestration, data observability, monitoring, and alerting to ensure pipeline reliability, data freshness, data quality, and timely issue detection.
• Maintain technical documentation, metadata, lineage, schema management, and data dictionaries to support governance, transparency, and operational support.
• Partner with business and technical stakeholders to translate requirements into scalable, sustainable data engineering solutions.
• Contribute to engineering best practices through code review, automated testing, version control, release management, and deployment standards.

• Bachelor’s degree in computer science, data engineering, information systems, engineering, or a related field; Masters preferred
• 3-5+ years of experience in data science/engineering, data warehousing, or analytics engineering.
• Advanced programming skills in Python and strong proficiency in SQL for building and maintaining production data pipelines across development and production environments.
• Experience developing scalable ELT/ETL pipelines and analytical or dimensional data models on relational, cloud, or distributed data processing platforms.
• Experience with Git, code review, automated testing, and modern software development practices.
• Strong understanding of data quality, troubleshooting, performance optimization, and production support.
• Experience integrating complex enterprise data across multiple source systems.

New York, New York Permanent USD115,000 - USD135,000 per year View Job Description

One of the nation’s top integrated academic health systems devoted to patient care, education, and research.