Data Engineer

Description Hart is a healthcare technology company focused on clinical data integration and archiving. We build the infrastructure that connects disparate health systems, providing a unified source of information for providers and patients. Job Summary We are looking for a Data Engineer to build and maintain our data infrastructure. You will be responsible for developing robust ETL/ELT pipelines and managing data workflows within the Databricks ecosystem. We need a builder who values simplicity and pragmatism—someone who can navigate the necessary rigor of a regulated industry without over-engineering technical solutions. While we are open to exceptional remote talent, we have a strong preference for candidates who can work on-site with us in Bozeman, MT.

Key Responsibilities Data Pipeline Development:

Design and implement scalable ETL/ELT pipelines to ingest and transform complex healthcare data.

Databricks Development:

Build and optimize data models and processing workflows within the Databricks ecosystem.

Pragmatic Engineering:

Focus on clean, maintainable code and simple solutions that solve the problem effectively without unnecessary complexity.

Performance Optimization:

Write and refine high-signal Python and SQL code to improve system reliability and efficiency.

AI/ML Support:

Develop the data foundation for machine learning workflows and assist in moving models into production.

Security & Compliance:

Ensure all data flows meet HIPAA and security standards through intentional documentation and validation. Culture We handle high-stakes data where precision is mandatory, but we solve those problems with an engineering-first mindset. This isn't a "corporate suit" environment—we are a meritocracy where the best idea wins, regardless of title. We value high-signal, direct communication and prioritize technical execution over unnecessary fluff. Our goal is to maintain a disciplined, professional standard for our systems while keeping our team structure lean and focused. If you prefer building foundational technology in a simple, pragmatic, and fluff-free environment, you will fit in here.

Requirements Professional Experience:

Proven track record in data engineering or a software engineering role with a heavy focus on data.

Databricks:

Hands-on experience with the Databricks platform.

Languages:

High proficiency in Python and

SQL. ETL/ELT

Experience building and maintaining production-grade data pipelines.

Cloud Infrastructure:

Experience working within AWS environments.

Preferred Qualifications AI/ML:

Experience with MLflow, model training, or integrating AI into data pipelines.

Healthcare Data:

Familiarity with healthcare standards like HL7 and FHIR.

Software Fundamentals:

Strong understanding of version control (Git) and CI/CD practices.