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# Founding Data Engineer

- **Company:** Patient Funding Alternatives
- **Location:** Woburn, MA, United States
- **Experience:** Expert
- **Salary:** $150,000.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Automation of Tests, Microsoft Azure, Hospital Information Systems, Cloud Computing, Code Review, Data Architecture, Data Cleansing, Information Engineering, Data Infrastructure, Data Systems, Data Visualization, Cursor (Graphical User Interface Elements), Database Design, Database Queries, Decision Support Systems, Python (Programming Language), Logistic Regression, Operational Databases, Performance Tuning, Power BI, Software Tools, Software Engineering, SQL Databases, Data Processing, Data Ingestion, GitHub Copilot, Fast Healthcare Interoperability Resources, Git, Solid Principles, Xgboost, Health Level Seven International, Data Management, Front End Software Development, GPT, Software Version Control, Data Pipelines, Serverless Computing
- **Published:** September 2, 2026
- **Apply:** https://www.wayup.com/i-j-Founding-Data-Engineer-Patient-Funding-Alternatives-035232161160229/

## About the Role

+ Senior-level experience building production data systems and analytical solutions
 + Expert-level Python - pipeline development, data manipulation, modeling, and backend engineering
 + Strong SQL proficiency - complex queries, performance optimization, and database design
 + Experience building predictive analytics models for a production environment (e.g. gradient boosting, RF, logistic regression)
 + Experience with hospital data systems and/or healthcare data standards (HL7, FHIR, claims data)
 + Proven track record working with messy, immature, or incomplete datasets - data cleaning and governance is part of the job, not a stepping stone to it
 + Experience integrating external data from third-party sources, APIs, or partner systems into a central data environment
 + Solid software engineering fundamentals: version control (Git), code reviews, automated testing, and software design principles
 + Experience building reporting layers and dashboards with Power BI or similar BI tools
 + Experience using modern AI-assisted software development tools such as GitHub Copilot, Claude Code, Cursor, Windsurf, or ChatGPT to accelerate engineering productivity
 + Ability to communicate complex technical findings clearly to non-technical executive stakeholders
 + Self-directed; thrives in ambiguous environments with limited oversight
Strongly Preferred

 + Healthcare industry experience - particularly hospital operations, revenue cycle, or patient financial services
 + Experience with hospital data systems and/or healthcare data standards (HL7, FHIR, claims data)
 + R proficiency for statistical analysis and modeling
 + Experience with healthcare EDI files (835/837 files)
 + Experience contributing to a re-platforming or system migration initiative
 + Familiarity with HIPAA requirements and handling of PHI
Nice to Have

 + JavaScript experience - particularly for data visualization layers or lightweight frontend integrations
 + Exposure to dbt, Airflow, or similar pipeline orchestration tooling
 + Experience in a PE-backed, high-growth, or early-stage company environment
 + Cloud platform experience (AWS, Azure, or GCP)

## Description

We are building PFA's data organization from the ground up. This is the first dedicated data hire and an opportunity to shape the architecture, standards, tooling, and analytical capabilities that will support the company for years to come. Every model you build and every pipeline you improve helps eligible families obtain healthcare coverage they otherwise might not receive.
You'll help build the intelligence platform behind Enable 2.0 by transforming fragmented healthcare data into predictive insights, AI-enabled workflows, and decision support systems that improve how patients access coverage and how hospitals operate. This is an opportunity to build a core strategic capability, not just maintain data pipelines.
As PFA grows, this role has significant opportunity to evolve into technical leadership for our expanding data organization.
_ What You'll Do_
Data Platform & Engineering

 + Own PFA's data platform, analytical infrastructure, and data engineering architecture
 + Help redesign and build the next-generation data architecture supporting Enable 2.0, including ingestion pipelines, APIs, analytical models, and cloud-native services
 + Build and maintain integrations for external data injections from hospital and healthcare data partners
 + Design and implement durable data cleaning and quality processes for immature, fragmented healthcare data - build repeatable pipelines, not one-off fixes
 + Design database schemas and data models that support both operational and analytical workloads
Analytics & AI

 + Work alongside our product and engineering teams to develop AI-driven capabilities including predictive modeling, intelligent workflow prioritization, and operational decision support
 + Derive actionable insights from complex hospital datasets and communicate findings clearly to non-technical leaders
 + Build reporting layers and dashboards using Power BI or similar BI tools
 + Develop analyses and models that inform decisions at the executive level
Software Engineering Practices

 + Write clean, well-documented, production-grade Python and SQL
 + Apply sound software design principles to data systems - modularity, maintainability, and scalability
 + Use version control (Git) and participate in code reviews as standard practice
 + Build automated testing into pipelines and data systems to ensure reliability
Ownership & Stakeholder Partnership

 + Serve as PFA's internal owner and subject matter expert for the data platform - the person leadership turns to for data decisions
 + Translate business questions from the CTO and operational leaders into well-scoped technical problems; communicate findings back in plain language
 + Proactively identify where data quality, coverage, or tooling gaps are limiting the business - and own the path to fixing them
 + Establish data best practices and standards as PFA's data organization grows


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