Healthcare Data Engineer -HDE3

REDi Health is a fast-growing healthcare technology services company focused on rural healthcare. The Healthcare Data Engineer is responsible for designing and implementing data pipelines, ensuring data quality and accuracy, and supporting analysts with reliable datasets.

Responsibilities:

• Designing and implementing pipelines and reusable datasets, ensuring consistent quality and accuracy
• Troubleshooting and resolving moderately complex technical issues
• Applying healthcare data context
• Documenting sources and transformations
• Supporting analysts and consultants with reliable, well-structured data
• Deliver accurate, timely, and repeatable pipeline outputs and analytics-ready datasets across multiple engagements
• Apply consistent quality assurance practices and validation checks to improve trust in outputs
• Contribute to reusable data models, standardized datasets, and scalable structures
• Support analysts and consultants by clarifying requirements and providing reliable datasets
• Mentor and share knowledge with junior engineers to strengthen team capability and adoption of standardized approaches
• Develop and maintain ingestion and transformation pipelines from source to analytics-ready output
• Troubleshoot moderately complex failures and coordinate resolution
• Improve reliability through automation, monitoring, and QA enhancements
• Incorporate healthcare data context to ensure pipelines meet domain-specific requirements and downstream analytic needs
• Build and refine reusable models that improve scalability across clients
• Strengthen documentation and definitions to reduce rework and ambiguity
• Support the development of standards, reusable structures, and best practices across engagements
• Support secure separation of client data across multi-tenant pipelines and shared environments
• Apply access controls, governance practices, and design patterns that ensure privacy and compliance
• Translate client and internal needs into structured technical requirements
• Support analysts by ensuring trusted, high-quality datasets are available
• Work with downstream users to clarify requirements, improve data usability, and ensure datasets meet analytic needs
• Provide guidance to junior engineers through review and support
• Communicate clearly in cross-functional technical discussions
• Mentor and share knowledge to strengthen team capability and promote adoption of repeatable, standardized approaches

Requirements:

• Typically 4–7 years of related data engineering or analytics experience
• Strong SQL and Python skills; experience with modern data stack tools
• Working understanding of healthcare revenue cycle, claims data, and EHR data systems
• Experience with reusable datasets, pipeline QA, and structured documentation practices
• Demonstrated ability to troubleshoot and resolve moderately complex technical issues
• Ability to apply healthcare data context to pipelines and datasets