Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.
Machinify builds AI-powered software that helps health plans pay claims accurately. As a Senior Data Engineer, you will design, build and run the data pipelines and models behind our payer-facing products, and help bring legacy data processes over into a common platform. You'll extend and integrate tooling along the way so the results can be reused by partner teams, not just our own.
This is a broad engineering role. You'll own pipelines end to end: ingestion, modeling, quality, deployment and day-to-day operations, in an AI-assisted engineering environment.
What You’ll Do
- Design, build and operate reliable, automated data pipelines for health plan data.
- Model complex, messy healthcare data into clear, trustworthy canonical and analytical models.
- Bring legacy processes, pipelines and models over into a common platform, preserving the logic and behavior that already work.
- Extend and integrate tools and workflows so other teams can adopt them.
- Build in data quality and software engineering discipline: validation, automated testing, code review, CI/CD.
- Document what you build and review AI-generated work critically.
What You Bring
- 5+ years in data engineering, including production ownership of the pipelines you built.
- Strong SQL and Python.
- Strong data modeling: canonical and dimensional design, conflicting sources, history, adjustments. You can explain why a model is shaped the way it is.
- Production dbt and workflow orchestration (Airflow or similar).
- Expertise with Snowflake and/or Databricks, Spark SQL experience
- Data quality and CI/CD practices applied to data: validation and reconciliation, pull requests, automated tests, deployment automation.
- Generalist range: you can take a broad, loosely defined problem and run it end to end across ingestion, modeling, infrastructure, APIs and operations, including incident response, and you onboard a new data source from discovery to delivery.
- A record of extending or integrating existing tools and building things other teams use.
- Quick, deep learning of complex domains: you ask why the data looks the way it does, and you verify AI-generated code and abstractions against ground truth.
- Good intuition on how to leverage AI in development and automation in day-to-day engineering practices, understands how to leverage AI as a force multiplier for efficiency, and potential risk
Strongly Preferred:
- Payment integrity experience, especially coordination of benefits and third-party liability (COB/TPL), cost avoidance, and Medicare Secondary Payer (MSP). Related areas such as post-pay audit, subrogation, overpayment recovery and claims editing are also of interest.
- Healthcare claims data experience (837/835/UB-04, eligibility, member and provider data, DRG).
- Experience building your own AI skills, MCP tools, and plugins
- Large-scale batch file ingestion (SFTP and cloud storage, EDI X12, fixed-width, CSV/Parquet) and schema drift handling.
- Automation: GitHub Actions, infrastructure-as-code, and turning recurring data operations into tested, repeatable workflows.
- experience with Scala
- Strong AWS experience.
- BI exposure, such as semantic or cube modeling.
- AI engineering: building your own agent tools, MCP servers, skills or plugins.
- Spark performance tuning, data contracts and schema governance, HIPAA/PHI handling.
🌱 Why Join Us
- Real impact — your pipelines will directly support decision-making and claims payment outcomes from day one.
- High visibility — partner with ML, Product, Analytics, Platform, Operations, and Customer teams on critical data initiatives.
- Total ownership — you’ll drive the lifecycle of core datasets powering our platform.
Customer-facing impact — you will directly contribute to successful customer onboarding and data integration.
What We Offer
- Work from anywhere in the US! Machinify is digital-first.
- Full Medical/Dental/Vision for employees & their families
- Flexible and trusting environment where you’ll feel empowered to do your best work
- Unlimited FTO
- Competitive salary, equity, 401(k) including employer match
The base salary range for this role is $180,000 - $220,000.
The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. We are hiring for different levels, and our Recruiting team will let you know if you qualify for a different role/range. Salary is one component of the total compensation package, which includes meaningful equity, excellent healthcare, flexible time off, and other benefits and perks.
Skills Required
- 5+ years of data engineering experience, including production ownership of built pipelines
- Strong SQL and Python skills
- Strong data modeling experience, including canonical and dimensional design, conflicting sources, history, and adjustments
- Production experience with dbt and workflow orchestration such as Airflow
- Expertise with Snowflake and/or Databricks
- Spark SQL experience
- Experience applying data quality and CI/CD practices, including validation, reconciliation, automated testing, pull requests, and deployment automation
- Ability to manage broad engineering problems across ingestion, modeling, infrastructure, APIs, operations, and incident response
- Experience extending or integrating existing tools and building reusable solutions for other teams
- Ability to learn complex domains quickly and verify AI-generated code against ground truth
- Understanding of AI-assisted development and automation practices, including associated risks
- Payment integrity experience, especially COB/TPL, cost avoidance, or MSP
- Healthcare claims data experience, including 837/835, UB-04, eligibility, member, provider, or DRG data
- Experience building AI skills, MCP tools, servers, or plugins
- Large-scale batch file ingestion and schema drift handling
- Experience with GitHub Actions, infrastructure as code, and automated recurring data operations
- Experience with Scala
- Strong AWS experience
- BI exposure, including semantic or cube modeling
- Spark performance tuning, data contracts, schema governance, or HIPAA/PHI handling experience
Machinify Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Machinify and has not been reviewed or approved by Machinify.
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Healthcare Strength — Health coverage is described as employer-paid for employees with additional support for dependents, alongside dental, vision, mental health, and FSA/HSA options. Listings consistently depict comprehensive medical benefits.
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Leave & Time Off Breadth — Policies include unlimited PTO, paid holidays and sick time, and a weekly no‑meetings day. These elements indicate broad time‑off access alongside flexible scheduling.
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Parental & Family Support — Inclusive paid parental leave is stated at 14 weeks for birth and non‑birth parents. Family benefits are prominently featured across public materials.
Machinify Insights
What We Do
Machinify is an AI start-up in the Healthcare space. Our software platform leverages the latest advances in machine learning, large language models, data analytics, and cloud processing to solve previously intractable problems in the healthcare industry impacting millions of lives.
Why Work With Us
We are a heavily cross-functional, collaborative diverse team working together to solve big problems that matter. If you are looking for an exciting environment where you'll be challenged to do the best work of your career, consider joining us!
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