Full Stack Engineer, Data Services

About the role

Description Of The Role As a Full Stack Engineer on Data Services, you will design, build, and maintain full-stack applications and services that enable clinicians and healthcare operations teams to access, visualize, and act on clinical data.

Primary Responsibilities

• Design and build full-stack features spanning React frontends, Python/FastAPI backends, and supporting data models and transformations
• Develop and maintain data models and transformation pipelines (dbt preferred) that feed application and analytics layers; ensure data flowing into applications is well-modeled, tested, and reliable
• Implement API contracts, versioning strategies, authentication/authorization patterns (OAuth/OIDC), and rate limiting for compliant clinical data access
• Build responsive, accessible React user interfaces with modern component patterns; collaborate with product and clinical teams to translate requirements into intuitive UIs
• Design and implement comprehensive testing strategies — unit tests, integration tests, end-to-end tests, and data validation tests — to ensure reliability across the stack
• Conduct and support QA activities including test planning, test case design, manual testing, and establishing testing standards; work closely with QA engineers and clinical testers to validate functionality and user experience
• Write clean, tested, maintainable code across the stack; participate actively in code review and help raise code quality standards
• Use AI-assisted development tools (Claude Code, GitHub Copilot, Cursor, or similar) deliberately and effectively — leveraging them for scaffolding, refactoring, test generation, and documentation while maintaining code quality and understanding
• Define and measure success metrics for features — including usage, adoption, clinical workflow impact, and data quality — to drive iterative improvements and prioritization
• Partner with product and data teams to establish KPIs and dashboards that measure feature impact on clinician workflows, care coordination, and operational efficiency
• Troubleshoot and resolve issues across the full stack — from UI bugs to API failures to data pipeline problems; trace issues end-to-end and implement durable fixes
• Collaborate with data engineering to ensure API data contracts are well-defined and upstream data models support application needs
• Support production systems through on-call rotations, incident response, and post-incident improvements
• Mentor junior engineers and contribute to team process improvement and knowledge sharing

Required Qualifications

• 3–5 years of professional software engineering experience, with demonstrated full-stack development capability
• Strong React proficiency with modern JavaScript (ES6+); comfortable building responsive, component-based, accessible user interfaces
• Strong Python skills with hands-on experience building REST APIs using FastAPI, Flask, Django, or comparable frameworks
• Demonstrated experience implementing authentication and authorization patterns such as OAuth 2.0 / OIDC or similar
• Proven experience designing data models, writing SQL, and building data transformation logic; understanding of normalization, dimensional modeling, or similar concepts
• Proven experience with testing frameworks and writing comprehensive tests (unit, integration, end-to-end); understanding of test coverage and QA best practices
• Experience defining, measuring, and acting on metrics and KPIs — understanding how to translate business requirements into measurable success criteria and iterate based on data
• Experience using AI coding assistants (Claude Code, GitHub Copilot, Cursor, ChatGPT) to improve development speed and quality — able to speak to how you use these tools effectively, not just that you have access
• Experience with version control (Git) and collaborative development workflows (pull requests, code review, CI/CD)
• Strong communication skills and ability to work cross-functionally with data, product, clinical, and engineering teams
• Comfortable working in ambiguous environments with evolving healthcare requirements; strong problem-solving and debugging skills

Strong Pluses

• Experience working with dedicated QA engineers or as a QA engineer; familiarity with QA methodologies, test case design, and testing in regulated environments
• Background in data-driven product development with experience defining and tracking OKRs, KPIs, or similar outcome metrics
• Experience with observability and monitoring tools (DataDog, CloudWatch, or similar); ability to define and track application health and performance metrics
• Experience with A/B testing, feature flags, or experimentation frameworks
• Experience with dbt for data transformation and testing; familiarity with medallion architecture (Bronze/Silver/Gold)
• Experience working with healthcare data and interoperability standards — familiarity with FHIR, HL7, claims data, EHR integrations, value-based care metrics, or care gap/attribution concepts
• Experience with cloud data platforms (Databricks, AWS, Snowflake)
• Familiarity with CI/CD pipelines, infrastructure-as-code, and containerization (Docker)
• Experience designing and consuming APIs; familiarity with API documentation standards (OpenAPI/Swagger)
• Background in healthcare, pharmaceutical, or other regulated industry with experience handling sensitive data
• Experience building and operating data quality validation and monitoring
• Familiarity with React testing libraries and frontend testing practices
• Previous experience on small, high-performing engineering teams in startup or high-growth environments