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. Client Details One of the nation's top integrated academic health systems devoted to patient care, education, and research. Description 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, Par Ex, GHX, People Soft, 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. MPI does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, marital status, or based on an individual's status in any group or class protected by applicable federal, state or local law.

MPI encourages applications from minorities, women, the disabled, protected veterans and all other qualified applicants. Profile A successful Data Engineer should have:
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. Job Offer Competitive salary ranging from $115,000 to $135,000 annually. Permanent, full-time position in New York. Interested? Apply today. MPI does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, marital status, or based on an individual's status in any group or class protected by applicable federal, state or local law.

MPI encourages applications from minorities, women, the disabled, protected veterans and all other qualified applicants.