Job description
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
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.