> Markdown version of [/jobs/ext/3070498-impact-oriented-data-engineer](https://www.wearedevelopers.com/jobs/ext/3070498-impact-oriented-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # impact-oriented Data Engineer - **Company:** Wider Circle - **Location:** United States (Remote available) - **Experience:** Experienced - **Salary:** $130,000.0 - $160,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Data Analysis, Cron, Customer Data Management, Data Definition Language, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Manipulation Languages, Database Queries, Software Debugging, Identity and Access Management, Data Intelligence, Python (Programming Language), Machine Learning, Operational Databases, Standard Sql, Salesforce.Com, SQL Stored Procedures, SQL Databases, Systems Integration, Workflow Management Systems, Application Enhancement Tool, Data Ingestion, Google Drive, Large Language Models, Reliability of Systems, Git, Pandas, Core Data, Production Code, Data Delivery, Data Pipelines, Api Management, Legacy Systems, Mulesoft, Amazon Redshift - **Published:** September 25, 2026 - **Apply:** https://startup.jobs/healthcare-data-engineer-wider-circle-10185845 ## About the Role * 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 ## 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., 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 ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [From clicks to cribs - How to find your dream home with web scraping](https://www.wearedevelopers.com/videos/767-from-clicks-to-cribs-how-to-find-your-dream-home-with-web-scraping) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) - [Getting to Know Your Legacy (System) with AI-Driven Software Archeology](https://www.wearedevelopers.com/videos/1437-getting-to-know-your-legacy-system-with-ai-driven-software-archeology) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)