Health IT Data Engineer — Secure Data Pipelines & Analytics

Aptive; United States; On-site; USD 110,000 - 150,000; Full time

Job summary

Aptive seeks a Health IT Data Engineer to support IHSC HITU IT modernization and enterprise data environments. You will design, build, and maintain secure data pipelines, data structures, and integration workflows enabling analytics across IHSC clinical, operational, and administrative domains.

The role uses Python, SQL, and ETL/ELT frameworks; optimizes data models for reporting; and implements data validation and quality controls.

Qualifications

• Advanced SQL, relational databases, and data modeling.
• Experience designing ETL/ELT pipelines and data integration with scripted development (Python).
• Familiarity with cloud-based analytics platforms and enterprise data environments.
• Understanding of healthcare or enterprise data environments.
• Strong analytical, problem-solving, and documentation skills.
• Ability to collaborate with technical and non-technical stakeholders.
• Ability to obtain DHS/ICE fitness determination and execute a DHS NDA.
• Authorized to work in the U.S.

Responsibilities

• Design, develop, and maintain scalable data pipelines from multiple sources.
• Support analytics platforms by optimizing data models, schemas, and performance for reporting/dashboards.
• Implement data validation and quality control processes for data assets.
• Collaborate with Data Strategists, Data Analysts, and Solutions Developers to enable analytics use cases.
• Maintain documentation for data architectures, pipelines, transformations, and dependencies.
• Support data governance initiatives including metadata management and lineage tracking.

Skills

SQL

Data Modeling

Python

ETL/ELT

Cloud Platforms

Healthcare Data

Documentation

Stakeholder Collaboration

Tools

Power BI

Tableau

Job description

Aptive seeks a Health IT Data Engineer to support IHSC HITU IT modernization and enterprise data environments. You will design, build, and maintain secure data pipelines, data structures, and integration workflows enabling analytics across IHSC clinical, operational, and administrative domains.

The role uses Python, SQL, and ETL/ELT frameworks; optimizes data models for reporting; and implements data validation and quality controls.