The Data Engineer is responsible for designing, building, and maintaining the organization's datainfrastructure to support a scalable, governed, and analytics-ready environment. This role focuses on thedevelopment of robust data pipelines, integration of disparate data sources, and optimization of data storageand processing frameworks, while contributing to the evolution of the WMed data platform toward a data-asa-service (DaaS) model that enables standardized, secure, and reusable access to trusted data assetsacross clinical operations, medical education, research, compliance, and executive decision-making.

Working within a modern data architecture, the Data Engineer transforms fragmented, system-centric datainto structured, reliable, and accessible datasets. This role partners closely with analysts, stakeholders, andtechnical teams to ensure data availability, integrity, and performance across platforms including partnerEHRs, academic systems, and enterprise applications. Please Note this is a Salaried Hybrid Position that will require on-site attendance. (MI residents only or willing to relocate - at their expense, to Michigan) This position is NOT eligible for employer-sponsored work authorization (visa sponsorship), now or in the future.

BENEFITS

Wellness reimbursement.

Continuing education and tuition reimbursement.

Employer-funded retirement plan.

Two medical plan options: PPO and High Deductible Health Plan (HDHP) with employer HSA contribution.

Flexible work solutions based on position and department.

Up to four weeks of PTO accrual beginning in year one.

Paid holidays.

Paid volunteer time.

Paid preferred holiday.

DUTIES AND RESPONSIBILITIES

Design, build, and maintain scalable data pipelines to ingest, transform, and load data from clinical, academic, and enterprise systemsDevelop and manage ETL processes using tools such as Pentaho and Microsoft SSIS, ensuring reliability and performanceDesign and implement data models and schemas to support downstream analytics and reporting use casesContribute to the development of a DaaS platform, enabling reusable, governed data products and standardized access patterns for analysts, applications, and self-service usersOptimize and maintain PostgreSQL data environments, including performance tuning and storage strategiesImplement and monitor data quality, validation, and error-handling processesEstablish and maintain data lineage, metadata, and documentation to support governance and transparencyIntegrate new data sources into the data platform, including APIs, flat files, and third-party systemsTroubleshoot and resolve data issues across the full data lifecycleSupport the evolution of organizational data architecture toward a modern, scalable platformContribute to standards, best practices, and governance frameworks for data engineeringAll other duties as assigned