Healthcare Data Engineer

Data Engineers serve a unique and critical role in daily operations at Wider Circle. Customer and program data are the bedrock of our business, and Data Engineering is responsible for building and maintaining the systems that power analytics, reporting, and product intelligence. We are looking for a hands-on, impact-oriented Data Engineer to build and maintain reliable data pipelines, modernize legacy workflows, and support analytics and machine learning use cases. You will primarily work within Amazon Web Services (AWS), supporting Amazon Redshift, Python-based pipelines, and lightweight AI/LLM integrations. This role requires someone who ships production code, improves system reliability, and partners closely with analytics and data science to ensure data is trustworthy, well-modeled, and actionable. You will join a talented, fully remote Data Science, Engineering & Analytics team that handles customer data processing, automation, product analytics, complex integrations, and data-driven innovation. Company Overview Wider Circle exists to create pathways to lasting connection, belonging, and well-being by bringing people together in circles of trust to support one another and strengthen our social fabric. We partner with health plans and community organizations to connect members in small, relationship-driven groups, where they can build trust, support one another, and take meaningful steps forward. By combining peer connection, local facilitators, and data-driven insights, we help members stay engaged in their health while enabling our partners to drive better outcomes at scale. Responsibilities Core Data Engineering 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 Orchestration & Automation 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 Analytics & Modeling Support 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 AI / LLM Integration 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 What Success Looks Like Data pipelines are reliable, observable, and well-documented Redshift schemas are clean, performant, and well-managed Analysts and stakeholders trust the data AI-powered tools meaningfully reduce engineering or analyst workload Internal SLAs for data delivery and quality are consistently met 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 Preferred Qualifications 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 Benefits Compensation The expected base salary range for this position is $130,000 – $160,000 per year. Actual compensation will depend on experience, qualifications, and location. As a venture-backed company, Wider Circle offers competitive compensation including: Performance-based incentive bonuses Opportunity to grow with the company Comprehensive health coverage including medical, dental, and vision 401(k) Plan Paid Time Off Employee Assistance Program Health Care FSA Dependent Care FSA Health Savings Account Voluntary Disability Benefits Basic Life and AD&D Insurance Adoption Assistance Program Training and Development And most importantly, an opportunity to make the world a better place! Wider Circle is proud to be an equal opportunity employer that does not tolerate discrimination or harassment of any kind. Our commitment to Diversity & Inclusion supports our ability to build diverse teams and develop inclusive work environments. We believe in empowering people and valuing their differences. We are committed to equal employment opportunity without consideration of race, color, religion, ethnicity, citizenship, political activity or affiliation, marital status, age, national origin, ancestry, disability, veteran status, sexual orientation, gender identity, gender expression, sex or gender, or any other basis protected by law. Originally posted on Himalayas