Healthcare Data Engineer

Wider Circle is a healthcare-focused company that connects people through relationship-driven groups and data-driven insights to improve well-being and health outcomes. The Healthcare Data Engineer will build and maintain reliable data pipelines, modernize legacy workflows, and support analytics, machine learning, and lightweight AI/LLM integrations using AWS, Redshift, Python, and SQL.

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