QA Engineer - Healthcare Data Platform
Job Title: QA Engineer (Healthcare Data Platform)
Location:
Remote
Position Type:
Contract/Contract-to-hire
About The Opportunity
We are a leading healthcare innovation organization with a nationwide footprint, delivering care to millions of individuals and communities across the U.S. Our mission is to improve health outcomes and make quality healthcare more accessible, affordable, and effective.
We’re seeking a QA Engineer to lead testing, validation, and quality assurance for a large-scale, cloud-based clinical quality measurement platform. This role is centered on ensuring release quality, system reliability, and runtime behavior across a distributed data processing engine operating at scale.
This is a high execution-focused role embedded within engineering teams, responsible for driving end-to-end QA strategy, system validation, and production-grade testing practices. The position emphasizes testing and quality engineering over data pipeline development, with a strong focus on validating complex data systems in real-world operating conditions.
Key Responsibilities
End-to-End QA & Testing Strategy
• Own and execute a comprehensive QA strategy including functional, regression, integration, and performance testing
• Embed testing early in the development lifecycle, ensuring quality is built in—not just validated post-deployment
• Define, evolve, and enforce QA standards, processes, and best practices across the platform
System & Data Validation
• Validate system inputs, outputs, and transformations within a clinical quality measurement engine
• Ensure accuracy, completeness, and consistency of healthcare data, including FHIR-based datasets
• Perform data reconciliation and validate explainability of system outputs
• Analyze logs, metrics, and runtime system behavior to identify defects and inconsistencies
Performance, Observability & Runtime Testing
• Design and execute load, stress, and performance testing scenarios across varying data volumes
• Validate system scalability, throughput, latency, and reliability under real-world conditions
• Leverage observability and logging tools to assess system health and diagnose issues
• Partner with engineering teams to ensure proper instrumentation for QA and production validation
Test Automation & CI/CD Integration
• Build and expand automated testing frameworks for functional and regression coverage
• Integrate QA processes into CI/CD pipelines for automated validation and release gating
• Ensure consistent, repeatable validation across environments and deployments
Platform & Infrastructure Validation
• Validate application behavior within containerized and distributed environments
• Collaborate with engineering teams to test and troubleshoot workloads running in Kubernetes
• Ensure system reliability across infrastructure layers, including orchestration and scaling behavior
Cross-Functional Collaboration
• Partner with engineers, product managers, and stakeholders to align testing efforts with system requirements
• Ensure consistency across all testing layers (unit, integration, QA, and UAT)
• Support UAT readiness and validation efforts with business stakeholders
Test Data Strategy & Risk Mitigation
• Develop strategies for synthetic and representative test data creation
• Design scalable datasets for performance and stress testing
• Ensure test data reflects real-world production scenarios
• Proactively identify risks related to data quality, availability, and system behavior
Required Qualifications
• Bachelor’s degree in Computer Science, Engineering, Health Informatics, or related field
• 5+ years of experience in QA engineering, software testing, or data validation-focused roles
• Strong experience with functional, regression, integration, and performance testing
• Experience testing distributed systems or data-intensive platforms
• Proficiency in SQL and data validation techniques
• Experience with test automation frameworks and CI/CD pipelines
• Strong ability to analyze logs, metrics, and runtime system behavior for debugging
• Working knowledge of cloud platforms (GCP preferred)
• Hands-on experience with Kubernetes (deployments, debugging, or testing in containerized environments)
• Strong analytical skills and attention to detail
Preferred Qualifications
• Experience working with healthcare data
• Familiarity with FHIRApply tot his job
Apply To this Job
Location:
Remote
Position Type:
Contract/Contract-to-hire
About The Opportunity
We are a leading healthcare innovation organization with a nationwide footprint, delivering care to millions of individuals and communities across the U.S. Our mission is to improve health outcomes and make quality healthcare more accessible, affordable, and effective.
We’re seeking a QA Engineer to lead testing, validation, and quality assurance for a large-scale, cloud-based clinical quality measurement platform. This role is centered on ensuring release quality, system reliability, and runtime behavior across a distributed data processing engine operating at scale.
This is a high execution-focused role embedded within engineering teams, responsible for driving end-to-end QA strategy, system validation, and production-grade testing practices. The position emphasizes testing and quality engineering over data pipeline development, with a strong focus on validating complex data systems in real-world operating conditions.
Key Responsibilities
End-to-End QA & Testing Strategy
• Own and execute a comprehensive QA strategy including functional, regression, integration, and performance testing
• Embed testing early in the development lifecycle, ensuring quality is built in—not just validated post-deployment
• Define, evolve, and enforce QA standards, processes, and best practices across the platform
System & Data Validation
• Validate system inputs, outputs, and transformations within a clinical quality measurement engine
• Ensure accuracy, completeness, and consistency of healthcare data, including FHIR-based datasets
• Perform data reconciliation and validate explainability of system outputs
• Analyze logs, metrics, and runtime system behavior to identify defects and inconsistencies
Performance, Observability & Runtime Testing
• Design and execute load, stress, and performance testing scenarios across varying data volumes
• Validate system scalability, throughput, latency, and reliability under real-world conditions
• Leverage observability and logging tools to assess system health and diagnose issues
• Partner with engineering teams to ensure proper instrumentation for QA and production validation
Test Automation & CI/CD Integration
• Build and expand automated testing frameworks for functional and regression coverage
• Integrate QA processes into CI/CD pipelines for automated validation and release gating
• Ensure consistent, repeatable validation across environments and deployments
Platform & Infrastructure Validation
• Validate application behavior within containerized and distributed environments
• Collaborate with engineering teams to test and troubleshoot workloads running in Kubernetes
• Ensure system reliability across infrastructure layers, including orchestration and scaling behavior
Cross-Functional Collaboration
• Partner with engineers, product managers, and stakeholders to align testing efforts with system requirements
• Ensure consistency across all testing layers (unit, integration, QA, and UAT)
• Support UAT readiness and validation efforts with business stakeholders
Test Data Strategy & Risk Mitigation
• Develop strategies for synthetic and representative test data creation
• Design scalable datasets for performance and stress testing
• Ensure test data reflects real-world production scenarios
• Proactively identify risks related to data quality, availability, and system behavior
Required Qualifications
• Bachelor’s degree in Computer Science, Engineering, Health Informatics, or related field
• 5+ years of experience in QA engineering, software testing, or data validation-focused roles
• Strong experience with functional, regression, integration, and performance testing
• Experience testing distributed systems or data-intensive platforms
• Proficiency in SQL and data validation techniques
• Experience with test automation frameworks and CI/CD pipelines
• Strong ability to analyze logs, metrics, and runtime system behavior for debugging
• Working knowledge of cloud platforms (GCP preferred)
• Hands-on experience with Kubernetes (deployments, debugging, or testing in containerized environments)
• Strong analytical skills and attention to detail
Preferred Qualifications
• Experience working with healthcare data
• Familiarity with FHIRApply tot his job
Apply To this Job