Machinify is the leading provider of AI-powered software products that transform healthcare claims and payment operations. Each year, the healthcare industry generates over $200B in claims mispayments, creating incredible waste, friction and frustration for all participants: patients, providers, and especially payers. Machinify’s revolutionary AI-platform has enabled the company to develop and deploy, at light speed, industry-specific products that increase the speed and accuracy of claims processing by orders of magnitude.
As a Data Engineer I, you’ll join a fast-paced, high-impact team focused on building scalable, reliable data systems that power our core AI-driven platform. You’ll work side-by-side with senior engineers, product managers, and data scientists to help ingest, standardize, and deliver data that drives critical healthcare and payment decisions.
You’ll play a hands-on role in turning messy, complex external data into structured, trustworthy datasets — learning best practices for data modeling, pipeline development, and production operations. This is a high-growth opportunity for someone who is curious, driven, and excited to learn the ropes of real-world data engineering.
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Build and maintain scalable data pipelines using Python, Spark SQL, and Airflow.
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Assist in onboarding new customers by helping transform their raw files (CSV, JSON, Parquet) into internal formats.
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Collaborate with senior engineers to improve data quality, observability, and reusability.
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Learn how to standardize external healthcare data (837 claims, EHR, etc.) into canonical internal models.
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Monitor and debug data pipeline issues with support from senior engineers.
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Work closely with analysts, scientists, and product managers to understand data requirements and business context.
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Participate in code reviews, design discussions, and debugging sessions.
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Contribute to documentation and internal tooling to improve team productivity.
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Grow your understanding of domain models, data contracts, and business context.
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Grow into owning workflows end-to-end, improving performance, and contributing to architectural decisions.
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Are a recent grad (BS/MS in CS, Data Engineering, or related field) or early-career engineer with 0–3 years of industry experience.
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Strong programming fundamentals and proficiency in Python.
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Exposure to SQL and a desire to work with large datasets.
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Curiosity about real-world data problems, particularly those involving messy, complex data.
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Hunger to learn — you enjoy getting into the weeds, asking good questions, and figuring things out.
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Solid communication skills — able to collaborate effectively with both technical and non-technical partners.
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Attention to detail and a strong sense of ownership.
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Prior internship or co-op in data engineering, analytics, or infra roles.
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Experience with cloud platforms like AWS, GCP, or Azure.
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Exposure to version control (e.g., Git), Docker, or CI/CD.
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Familiarity with distributed data processing (Spark, Hadoop, etc.)
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Contributions to open-source, side projects, or technical blogs.
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Mentorship & Growth: Learn from senior engineers, with opportunities for rapid growth.
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Mission-driven — Help shape the future of AI-powered decision-making in healthcare.
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Impact from Day One: Real ownership. Real systems. Real users.
If you’re looking to kick-start your career in data engineering and want to work on real problems with real impact — let’s talk.
Equal Employment Opportunity at Machinify
Machinify is committed to hiring talented and qualified individuals with diverse backgrounds for all of its positions. Machinify believes that the gathering and celebration of unique backgrounds, qualities, and cultures enriches the workplace.
