Vytalize Health - Full Stack Engineer, Data Services
Requirements
• 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 • Experience implementing authentication and authorization patterns such as OAuth 2.0 / OIDC or similar • Demonstrated 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 • Proven 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 • Exposure to healthcare compliance requirements (HIPAA, PHI/PII handling, audit logging) • Familiarity with React testing libraries and frontend testing practices • Previous experience on small, high-performing engineering teams in startup or high-growth environments • This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee. Other duties, responsibilities, and activities may change or be assigned at any time with or without notice.
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 • Design and implement REST APIs serving clinical data, quality metrics, care gaps, and decision support content to internal applications and external partners • 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 • Participate in architecture and design discussions including API design, authentication patterns, data contract definition, and system reliability • Raise data quality or data modeling concerns early in the development process rather than letting them surface downstream • Contribute to technical documentation including API specifications, data dictionaries, runbooks, and architectural decisions • 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
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