Healthcare Data Engineer

Wider Circle connects health plan members and community organizations through relationship-driven groups, data-driven insights, and support for better health outcomes. The Healthcare Data Engineer will build and maintain reliable data pipelines, modernize legacy workflows, support analytics and machine learning use cases, and integrate lightweight AI/LLM utilities while ensuring data quality, security, and observability.

Responsibilities:

• Build and maintain scalable ETL/ELT pipelines using Python (pandas) and SQL
• Ingest data from Amazon S3, APIs, Salesforce, and internal systems
• Write performant SQL in Amazon Redshift (DDL, DML, stored procedures)
• Manage schemas, views, permissions, and table evolution safely
• Debug production data issues and performance bottlenecks
• Ensure data quality, freshness, lineage, and observability
• Document pipelines and datasets clearly
• Ensure appropriate data safeguards for sensitive and regulated data, including PHI and PII
• Migrate legacy cron-based workflows to more robust orchestration frameworks
• Implement idempotent, retry-safe, production-ready jobs
• Improve reliability and monitoring of existing pipelines
• Use Git for version control and CI-friendly development practices
• Partner with Analytics and Data Science to provide clean, modeled datasets
• Support BI tools, reporting workflows, and Google Sheets integrations
• Ensure internal SLAs for data quality and delivery frequency are met
• Provide expert support for complex data integration challenges
• Build lightweight AI-powered utilities (e.g., metadata extraction, SQL generation, anomaly explanation)
• Integrate LLM APIs into existing data workflows
• Focus on practical augmentation that saves analyst and engineer time

Requirements:

• 3-6 years of experience in data engineering or analytics engineering
• Strong Python skills (dataframes, file I/O, APIs)
• Strong SQL skills, including warehouse-specific optimization
• Hands-on experience with AWS (S3, IAM, Redshift)
• Experience using APIs for data ingestion and system integration
• Experience with Git and collaborative development workflows
• Comfortable working with imperfect data and legacy systems
• Experience replacing cron with modern orchestration tools (e.g., Airflow or similar)
• Experience with Salesforce API integrations
• Familiarity with Google Drive / Google Sheets APIs
• Exposure to LLM APIs (OpenAI, Anthropic, etc.)
• Experience working with healthcare data (claims, eligibility, CDAs/HRAs)
• Experience partnering with Data Scientists to productionalize models
• Experience with tools such as Matillion, Mulesoft, or similar