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Salary: USD 196,000 - 230,000 / annual
Komodo Health is seeking a Senior Data Platform Engineer to join the Data Foundations team and play a critical role in shaping the core data products that fuel the Healthcare Map—the industry's largest, most complete view of the U.S. healthcare system. This hands-on engineering role focuses on transforming massive, complex healthcare datasets into performant, trustworthy, and usable data assets that power both customer-facing applications and internal product innovation.
In this role, you will design, build, operate, and improve large-scale data pipelines and foundational data products that power Komodo's Healthcare Map, analytics products, and downstream AI/ML-enabled use cases. You will work on processing complex healthcare data at scale, improving reliability and performance, and contributing to the technical direction of core data systems.
Key responsibilities include:
- Build, operate, and optimize large-scale production data pipelines using Python, SQL, Airflow, cloud infrastructure, and distributed processing frameworks
- Transform massive healthcare claims, EHR, and reference datasets into trusted, performant Healthcare Map data products and serving-ready data assets
- Strengthen pipeline reliability through data quality checks, validation, lineage, observability, monitoring, and alerting
- Debug complex data, system, and performance issues across computationally intensive workflows
- Partner with Data Product Quality, Product, Platform, and Engineering teams to translate healthcare data needs into scalable technical solutions
- Contribute to system design, architecture, code quality, testing, documentation, CI/CD, and rotational production support
- Enable downstream analytics, product, and AI/ML use cases through high-quality, well-modeled, reliable data
- Mentor team members through design reviews and engineering best practices
Over your first 12 months, you will deliver high-impact technical initiatives that improve pipeline performance and scalability, harden core Data Foundations systems for reliability and cost-efficiency, develop deep domain expertise in healthcare data challenges such as patient journey mapping and identity resolution, and ship scalable, production-grade data solutions in partnership with cross-functional teams.
Komodo Health operates a hybrid model with hubs in San Francisco, New York City, and Chicago. This role is open to US remote or SF/NYC hybrid arrangements.
REQUIREMENTS:
- Healthcare data experience across claims, clinical, RWE, provider, patient, or life sciences datasets, including coding systems such as ICD-10, CPT, NDC, or NPI
- Strong hands-on experience building, operating, and debugging production-grade data pipelines at scale
- Advanced Python and SQL skills, with experience in Airflow or similar workflow orchestration tools
- Experience with Spark or comparable distributed data processing frameworks
- Proven experience designing and operating data solutions in AWS
- Strong instincts for data quality, reliability, root-cause analysis, and production troubleshooting
- Ability to communicate technical trade-offs clearly and collaborate with engineering, product, and data partners
- Comfort using AI-assisted engineering tools (ChatGPT, Gemini, Claude, etc.) for productivity, debugging, documentation, and technical exploration
NICE-TO-HAVE:
- Experience delivering external-facing data products through customers, APIs, serving layers, or production access patterns
- Ability to optimize high-scale data architectures for performance, cost, versioning, and large-volume productization
- Experience applying AI or agentic workflows to engineering, data quality, delivery, or operations
- Success in high-growth or ambiguous environments that require balancing architecture, speed, and quality
