Healthcare Data & Integration Engineer

compasshealthcenter; Chicago (IL); On-site; USD 110,000 - 170,000; Full time

Job summary

Compass Health Center seeks a Data & Integration Engineer to build and maintain a scalable data platform, pipelines, and integrations across clinical, operational, financial, and business systems.

You will enable analytics and AI-enabled workflows by centralizing data, standardizing processes, and ensuring data security and governance. This role collaborates with analysts and stakeholders to translate needs into robust data solutions.

Qualifications

• Bachelor's degree or equivalent in a related field.
• 5+ years of experience in data engineering, data integration, software engineering, BI engineering, or related work.
• Experience building and supporting production data pipelines and integrations.
• Strong SQL skills and experience with relational and analytical data.
• Experience with Python, PySpark, or similar data transformation technologies.
• Experience with ETL/ELT, APIs, data modeling, data quality, and integration patterns.
• Experience working with modern cloud data platforms.
• Ability to independently troubleshoot complex data and integration issues.
• Ability to turn business and analytical needs into scalable technical solutions.
• Strong documentation, communication, and cross-functional partnership skills.
• Understanding of data security, access controls, privacy, and handling of sensitive information.

Responsibilities

• Build, maintain, and improve data pipelines, integrations, transformations, lakehouse structures, and data models.
• Bring data from EMR/EHR, finance, HR, CRM, scheduling, payer, and other systems into a governed data platform.
• Use SQL, Python/PySpark, APIs, dataflows, notebooks, connectors, gateways, and other appropriate tools to move and transform data.
• Replace manual, file-based, or fragile processes with reliable and scalable solutions.
• Build integrations between cloud based, and SaaS systems.
• Evaluate new data sources and determine the best approach for ingestion, integration, and ongoing support.
• Monitor pipelines, refreshes, integrations, and data quality and troubleshoot failures.
• Build logging, alerting, error handling, and recovery processes.
• Resolve issues related to source-system changes, schemas, credentials, gateways, and data availability.
• Improve the reliability, performance, and maintainability of existing data workflows.
• Reduce dependencies on individual users, workstations, manual file movement, and undocumented processes.
• Maintain clear documentation, lineage, naming standards, and technical ownership of data assets.
• Support appropriate data access, security, privacy, and handling of PHI and other sensitive information.
• Build trusted data foundation for reporting, self-service analytics, and AI-enabled analysis.
• Partner with analysts and business owners to understand data requirements, definitions, quality issues, and priorities.
• Structure and document data for Power BI, advanced analytics, and AI workflows.
• Partner with Senior Clinical Data Analyst and Technology leadership to enable analytics and AI capabilities.
• Establish scalable patterns for governed data access.
• Identify opportunities to use Microsoft Fabric and related tools to improve engineering, integration, quality, and automation.
• Cross-functional collaboration with Analytics, Infrastructure, Security, EMR, application owners, and vendors when data crosses systems.

Skills

SQL

Python/PySpark

ETL/ELT

Data modeling

Data integration

Cloud data platforms

Documentation

Cross-functional collaboration

Troubleshooting

Education

Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or related field

Equivalent relevant experience

Tools

Microsoft Fabric

Power BI

APIs

Job description

Compass Health Center seeks a Data & Integration Engineer to build and maintain a scalable data platform, pipelines, and integrations across clinical, operational, financial, and business systems.

You will enable analytics and AI-enabled workflows by centralizing data, standardizing processes, and ensuring data security and governance. This role collaborates with analysts and stakeholders to translate needs into robust data solutions.