Position SummaryAs a Senior Engineer specializing in Healthcare Effectiveness Data and Information Set (HEDIS) measures and clinical quality data, you will lead the architecture, transformation, and optimization of clinical data solutions using Snowflake and AI/ML technologies. You will partner with business analysts, clinical quality leaders, and data science teams to build scalable, AI-enhanced data pipelines that streamline HEDIS reporting, automated chart abstraction, quality measure analytics, and care gap identification. This role combines deep healthcare domain expertise in HEDIS/Stars with modern cloud data platform engineering and AI capabilities.
Primary Responsibilities- Design, build, and maintain scalable data pipelines in Snowflake to ingest, transform, and manage complex clinical and claims data for HEDIS measure processing
- Integrate Artificial Intelligence and Machine Learning models (such as natural language processing and predictive analytics) into Snowflake data workflows to automate clinical data extraction and care gap identification
- Optimize Snowflake queries, data models, snowpipes, and data warehouse performance for large-scale healthcare data analytics
- Collaborate with clinical quality, Stars, and reporting teams to translate NCQA/HEDIS specification requirements into technical logic and automated data workflows
- Implement robust data quality checks, data governance, security protocols, and HIPAA-compliant data practices across all Snowflake and AI pipelines
- Mentor junior engineers and collaborate with cross-functional technical teams to continuously refine technical architecture and MLOps/DataOps practices
- Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI
You9ll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
Required Qualifications- 6+ years of experience in data engineering, software engineering, or data warehouse architecture within the healthcare industry
- 3+ years of hands-on experience designing, developing, and optimizing data solutions on Snowflake (including SQL, Snowpark, or data modeling)
- 3+ years of experience developing in Python, SQL, or Scala for automated data processing
- 2+ years of experience integrating Artificial Intelligence, Machine Learning, or Natural Language Processing (NLP) models into data pipelines
Preferred Qualifications- Bachelor9s or Master9s degree in Computer Science, Data Engineering, Healthcare Informatics, or a related technical field
- 3+ years of experience with Healthcare Effectiveness Data and Information Set (HEDIS) measures, clinical quality data, or medical claims processing
- Experience with Snowpark Python/Java or Cortex AI capabilities within Snowflake
- Experience with NCQA HEDIS digital measure specifications (e.g., dQMs, FHIR, Quality Data Model)
- Experience with cloud orchestration tools and CI/CD pipelines (e.g., Airflow, Azure DevOps, Jenkins, Docker)
*All Telecommuters will be required to adhere to UnitedHealth Group9s Telecommuter Policy.
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you9ll find a far-reaching choice of benefits and incentives. The salary for this role will range from $91,700 to $163,700 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
