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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 be responsible for processing complex healthcare data at scale, improving reliability and performance, and contributing to the technical direction of core data systems.
Key responsibilities include:
- Building, operating, and optimizing large-scale production data pipelines using Python, SQL, Airflow, cloud infrastructure, and distributed processing frameworks
- Transforming massive healthcare claims, EHR, and reference datasets into trusted, performant Healthcare Map data products and serving-ready data assets
- Strengthening pipeline reliability through data quality checks, validation, lineage, observability, monitoring, and alerting
- Debugging complex data, system, and performance issues across computationally intensive workflows
- Partnering with Data Product Quality, Product, Platform, and Engineering teams to translate healthcare data needs into scalable technical solutions
- Contributing to system design, architecture, code quality, testing, documentation, CI/CD, and rotational production support
- Enabling downstream analytics, product, and AI/ML use cases through high-quality, well-modeled, reliable data
- Raising the bar across the team through mentorship, 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 partner with cross-functional teams to ship scalable, production-grade data solutions.
Komodo expects you to leverage AI-augmented engineering tools (ChatGPT, Gemini, Claude) to improve productivity and technical decision-making, including code generation, documentation, test case creation, debugging, and architectural assessment.
The company offers a hybrid work 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 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
