IT Data Engineer

Western Michigan University Homer Stryker M.D. School of Medicine; Kalamazoo (MI); Hybrid; USD 90,000 - 130,000; Full time

Benefits offered by this job

Wellness reimbursement

Tuition reimbursement

Retirement plan

Health insurance—medical plans

Flexible work solutions

Paid time off

Paid holidays

Volunteer time

Job summary

Western Michigan University Homer Stryker M.D. School of Medicine is seeking a Data Engineer to design, build, and maintain scalable data pipelines across clinical, academic, and enterprise systems.

The role focuses on ETL, data models, and governance to enable analytics-ready data assets. You will optimize PostgreSQL environments, contribute to a DaaS platform, and collaborate with analysts and technical teams to ensure data availability and quality.

Qualifications

• Able to design scalable data pipelines across clinical, academic, and enterprise systems.
• Experience with ETL tools (Pentaho, SSIS) and relational databases (PostgreSQL).
• Knowledge of data governance, data quality, and metadata management.

Responsibilities

• Design, build, and maintain scalable data pipelines ingesting data from multiple sources.
• Develop and manage ETL processes ensuring reliability and performance.
• Design data models and schemas to support analytics and reporting.
• Contribute to a DaaS platform for governed, reusable data products.
• Optimize PostgreSQL environments and implement data quality checks.
• Establish data lineage, metadata, and documentation for governance.
• Integrate new data sources via APIs, flat files, and third-party systems.
• Troubleshoot data issues across the data lifecycle and improve architecture.

Skills

Data pipeline design

ETL development

Data governance

Data quality

Metadata management

SQL & PostgreSQL tuning

Troubleshooting data issues

Collaboration with analysts

Communication

Tools

Pentaho

SSIS

PostgreSQL

APIs

Job description

The Data Engineer is responsible for designing, building, and maintaining the organizations data infrastructure to support a scalable, governed, and analytics-ready environment. This role focuses on the development of robust data pipelines, integration of disparate data sources, and optimization of data storage and 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 assets across clinical operations, medical education, research, compliance, and executive decision-making. Working within a modern data architecture, the Data Engineer transforms fragmented, system-centric data into structured, reliable, and accessible datasets. This role partners closely with analysts, stakeholders, and technical teams to ensure data availability, integrity, and performance across platforms including partner EHRs, 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 systems. Develop and manage ETL processes using tools such as Pentaho and Microsoft SSIS, ensuring reliability and performance. Design and implement data models and schemas to support downstream analytics and reporting use cases. Contribute to the development of a DaaS platform, enabling reusable, governed data products and standardized access patterns for analysts, applications, and self-service users. Optimize and maintain PostgreSQL data environments, including performance tuning and storage strategies. Implement and monitor data quality, validation, and error-handling processes. Establish and maintain data lineage, metadata, and documentation to support governance and transparency. Integrate new data sources into the data platform, including APIs, flat files, and third-party systems. Troubleshoot and resolve data issues across the full data lifecycle. Support the evolution of organizational data architecture toward a modern, scalable platform. Contribute to standards, best practices, and governance frameworks for data engineering. All other duties as assigned.