Data Engineer with Python and React - Remote

Glint Tech Solutions LLC

$90K — $130K *
Healthcare
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of hands-on experience in Python for data engineering
  • Familiarity with data frameworks (Pandas, PySpark, Airflow)
  • Basic or strong skills in React.js frontend development
  • Proficient in building scalable ETL/ELT pipelines
  • Solid understanding of REST APIs and system integrations
  • Experience with both relational and NoSQL databases
  • Familiarity with cloud platforms (AWS, Azure, or GCP)

Responsibilities

  • Build and maintain web applications using Python and React
  • Design and develop scalable data pipelines and dashboards for healthcare
  • Create ETL/ELT pipelines for healthcare datasets
  • Work with EHR integration and interoperability platforms
  • Develop internal tools and analytics platforms for healthcare teams
  • Ensure applications meet HIPAA and compliance standards
  • Collaborate with teams across the organization including engineers and clinicians

Benefits

  • Remote work flexibility
  • Opportunity to impact healthcare through data solutions
  • Collaborative team environment
  • Professional growth and development opportunities
  • Exposure to cutting-edge technologies in healthcare
  • Work in a mission-driven organization focused on improving healthcare outcomes
Full Job Description
About the job Data Engineer with Python and React - Remote

Overview

We are seeking a Data Engineer with strong experience in Python and React to build and maintain scalable data-driven applications and platforms in the healthcare domain.

What You'll Do
  • Build and maintain data-driven web applications using Python (backend/data engineering) and React (frontend)
  • Design and develop scalable data pipelines, APIs, and frontend dashboards for healthcare workflows
  • Build ETL/ELT pipelines to process clinical, operational, and healthcare datasets
  • Work with healthcare data systems including EHR integrations and healthcare interoperability platforms
  • Develop internal tools, analytics platforms, and operational dashboards for clinicians, administrators, and healthcare operations teams
  • Integrate with healthcare data standards and systems (e.g., HL7, FHIR, Epic, Cerner environments where applicable)
  • Design and optimize data models, warehouses, and data processing workflows
  • Translate healthcare operational and reporting requirements into scalable data solutions
  • Ensure applications and data platforms meet security, privacy, and compliance requirements (HIPAA-aligned environments)
  • Monitor, debug, optimize, and maintain production data systems and applications
  • Collaborate with cross-functional stakeholders including data analysts, clinicians, operations teams, and software engineers

Required Skills & Experience
  • Strong hands-on experience with Python for data engineering and backend development
  • Experience with data processing frameworks and libraries (Pandas, PySpark, Airflow, SQLAlchemy, etc.)
  • Basic to strong experience with React.js frontend development
  • Experience building scalable ETL/ELT pipelines and production-grade data applications
  • Strong understanding of REST APIs and system integrations
  • Experience working with relational and/or NoSQL databases
  • Experience with data warehousing, data modeling, and large-scale data processing
  • Familiarity with cloud platforms and data services (AWS, Azure, or GCP preferred)
  • Ability to work in ambiguous, real-world problem spaces
  • Strong communication skills with technical and non-technical stakeholders
  • Bachelor's degree in Computer Science, Engineering, or equivalent experience

Preferred Experience
  • Prior experience in healthcare technology or healthcare systems
  • Familiarity with HL7, FHIR, or EHR systems (e.g., Epic, Cerner)
  • Experience working with healthcare workflows (clinical, operational, or administrative systems)
  • Exposure to regulated environments (HIPAA, security-sensitive systems)
  • Experience with big data technologies and distributed processing systems
  • Experience building analytics dashboards or data visualization platforms
  • Experience working with enterprise-scale data platforms and pipelines

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