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

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)
Bachelor's degree in Computer Science, Engineering, or equivalent experience
Ability to work in ambiguous, real-world problem spaces
Strong communication skills with technical and non-technical stakeholders.

Data Engineer, Python, React

Key skills