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Salary: USD 130,000 - 160,000 / annual
Wider Circle is seeking a hands-on Data Engineer to build and maintain reliable data pipelines that power analytics, reporting, and product intelligence for a healthcare-focused platform. The company connects members in relationship-driven groups to support health and well-being, partnering with health plans and community organizations.
You will work within a fully remote Data Science, Engineering & Analytics team, primarily using Amazon Web Services (AWS), Amazon Redshift, and Python-based pipelines. Your responsibilities span core data engineering, orchestration, analytics support, and lightweight AI/LLM integration.
Core responsibilities include:
- Building and maintaining scalable ETL/ELT pipelines using Python (pandas) and SQL
- Ingesting data from Amazon S3, APIs, Salesforce, and internal systems
- Writing performant SQL in Amazon Redshift (DDL, DML, stored procedures)
- Managing schemas, views, permissions, and table evolution
- Debugging production data issues and performance bottlenecks
- Ensuring data quality, freshness, lineage, and observability
- Migrating legacy cron-based workflows to robust orchestration frameworks
- Implementing idempotent, retry-safe, production-ready jobs
- Partnering with Analytics and Data Science teams to provide clean, modeled datasets
- Supporting BI tools, reporting workflows, and Google Sheets integrations
- Building lightweight AI-powered utilities (e.g., metadata extraction, SQL generation, anomaly explanation)
- Integrating LLM APIs into existing data workflows
Success means reliable, observable, well-documented pipelines; clean, performant Redshift schemas; trusted data; meaningful AI-powered tools; and consistent internal SLAs for data delivery and quality.
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
