Data Engineer - FHIR Expertise

1 month, 3 weeks ago
Full-time
Lead
Software Development

Walter

Walter is a remote staffing and recruitment agency that connects companies with vetted remote talent from Latin America and the Philippines, offering support for sourcing, screening, interviews, onboarding, and a 12-month replacement guarantee.

Recruiting, staffing, remote hiring, talent acquisition

Description

  • Develop and enhance AI-powered medical assistant data solutions for healthcare systems.
  • Optimize patient recommendations and integrate medical policy guidance into AI workflows.
  • Support health system submissions data through data solution design and implementation.
  • Lead data extraction and data management efforts across large and complex datasets.
  • Spearhead big data and cloud-based data integration initiatives.
  • Conduct FHIR audits and create data mapping to streamline clinical workflows.
  • Work with HL7 JSON and related healthcare data formats.
  • Support nursing staff operations with advanced data solutions.
  • Collaborate on managing complex healthcare workflows and system integration needs.

Requirements

  • Expertise in data engineering and data management with large datasets.
  • Proficiency with FHIR (Fast Healthcare Interoperability Resources).
  • Strong background in Healthcare IT and clinical workflow processes.
  • Previous experience with Epic Clarity.
  • Experience with HL7 JSON.
  • Experience with health systems management and nursing operations support (nice to have).
  • Knowledge of insurance company integration with medical policy recommendations (nice to have).
  • Familiarity with developing smart apps that improve patient history and data accessibility (nice to have).
  • Ability to start immediately.
  • Commitment to a full-time engagement for 3 to 6 months in the US.

Benefits

  • Full-time engagement.
  • 3 to 6 month duration.
  • Immediate start.
  • US-based opportunity.

Interested in this position?

Apply directly on the company website

Apply Now

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