About Care Continuity
Care Continuity is redefining patient navigation. We combine clinical expertise, AI-driven insights, and compassionate human support to ensure patients receive the care they need - when and where they need it. Our solutions empower health systems and providers to close care gaps, reduce readmissions, and drive ROI through smarter, more connected navigation.
Our work is transforming how care decisions are made - and we're just getting started.
About the Role
You'll be responsible for designing and implementing scalable, reliable ETL pipelines that power our core data platform.
You'll collaborate closely with product, data analytics, data science, and engineering to understand requirements and ensure data pipelines align with end-user needs. You'll also help shape our data infrastructure, build reusable transformation logic, and enforce best practices for data quality and governance.
This is a high-ownership role for someone excited to solve complex data problems at the intersection of healthcare, analytics, and product development.
What You'll Do
Design scalable data models to support downstream analysis and reporting
Create and optimize data pipelines for efficient data processing, ensuring data is readily available for data scientists and analysts
Help define data engineering standards, tooling, and architecture as we scale
Implement data quality checks, logging, and monitoring for reliability and transparency
Collaborate with product, data analytics, and data science to translate requirements into robust data workflows
Collaborate with engineering to define and implement ingestion across data sources
Write clean, testable code for transformation logic and pipeline orchestration
Produce clear documentation and runbooks
What We're Looking For
3–6+ years of experience in data engineering, building production data pipelines
Strong experience with ETL pipeline development using modern tools (e.g., Airflow, dbt, Spark, etc.)
Proficiency in Python, SQL, and NoSQL databases
Experience working with HL7 CDA / CCD documents, FHIR resources, or other healthcare data formats
Experience designing data models for analytics and machine learning
Strong problem-solving mindset and willingness to dive into ambiguity
Nice to Have
Healthcare data experience (e.g., SNOMED, ICD-10, CDA)
Experience building data pipelines in cloud environments (AWS, GCP, Azure)
Experience with dbt or similar transformation layer tools
Exposure to predictive modeling or ML pipelines is a plus
Salary \& Benefits
Estimated salary range: $130,000 - $155,000, depending on skills and experience
Comprehensive benefits package, including medical, dental, vision, and 401(k)
Equity opportunities
Flexible PTO and fully remote work environment