Data Engineer I

Summary

Join Machinify, a leading provider of AI-powered healthcare software, as a Data Engineer I. You will be part of a fast-paced team building scalable data systems for our AI platform. Collaborate with senior engineers, product managers, and data scientists to ingest, standardize, and deliver data for critical healthcare and payment decisions. Transform complex external data into structured datasets, learning data modeling, pipeline development, and production operations. This is a high-growth opportunity to learn real-world data engineering. You will build and maintain data pipelines, onboard new customers, improve data quality, and work with various teams to understand data requirements. Grow your understanding of domain models and contribute to architectural decisions.

Requirements

• Are a recent grad (BS/MS in CS, Data Engineering, or related field) or early-career engineer with 0–3 years of industry experience
• Strong programming fundamentals and proficiency in Python
• Exposure to SQL and a desire to work with large datasets
• Curiosity about real-world data problems, particularly those involving messy, complex data
• Hunger to learn — you enjoy getting into the weeds, asking good questions, and figuring things out
• Solid communication skills — able to collaborate effectively with both technical and non-technical partners
• Attention to detail and a strong sense of ownership

Responsibilities

• Build and maintain scalable data pipelines using Python, Spark SQL, and Airflow
• Assist in onboarding new customers by helping transform their raw files (CSV, JSON, Parquet) into internal formats
• Collaborate with senior engineers to improve data quality, observability, and reusability
• Learn how to standardize external healthcare data (837 claims, EHR, etc.) into canonical internal models
• Monitor and debug data pipeline issues with support from senior engineers
• Work closely with analysts, scientists, and product managers to understand data requirements and business context
• Participate in code reviews, design discussions, and debugging sessions
• Contribute to documentation and internal tooling to improve team productivity
• Grow your understanding of domain models, data contracts, and business context
• Grow into owning workflows end-to-end, improving performance, and contributing to architectural decisions

Preferred Qualifications

• Prior internship or co-op in data engineering, analytics, or infra roles
• Experience with cloud platforms like AWS, GCP, or Azure
• Exposure to version control (e.g., Git), Docker, or CI/CD
• Familiarity with distributed data processing (Spark, Hadoop, etc.)
• Contributions to open-source, side projects, or technical blogs

Benefits

• Mentorship & Growth : Learn from senior engineers, with opportunities for rapid growth
• Mission-driven — Help shape the future of AI-powered decision-making in healthcare
• Impact from Day One : Real ownership. Real systems. Real users