Senior Data Platform Engineer — AI-Driven Healthcare Data

Komodo Health, Inc.; New York (NY); Hybrid; USD 196,000 - 230,000; Full time

Job summary

Komodo Health, Inc. is seeking a Senior Data Engineer to design, build, and operate large-scale data pipelines powering the Healthcare Map. You will transform vast healthcare data into reliable, analysis-ready assets and collaborate across Data Product, Platform, and Engineering teams to deliver production-grade solutions.

You will contribute to system design, data quality, and observability while working in a hybrid US-based environment with potential remote opportunities.

Qualifications

• Experience building production data pipelines at scale.
• Strong Python and SQL skills with data modelling experience.
• Familiarity with Airflow or similar orchestration tools.
• Experience with Spark or distributed data processing frameworks.
• Proven ability to design and operate data solutions in AWS.

Responsibilities

• Build, operate, and optimize large-scale production data pipelines using Python, SQL, Airflow, cloud infrastructure, and distributed processing frameworks.
• Transform healthcare datasets into trusted data assets for Analytics and AI use cases.
• Improve data quality, validation, lineage, observability, monitoring, and alerting.
• Debug complex data, system, and performance issues in large workflows.
• Collaborate with Data Product, Platform, and Engineering teams to translate data needs into scalable solutions.
• Contribute to system design, testing, documentation, CI/CD, and production support.

Skills

Python

SQL

Data pipelines

Distributed processing

Data quality

AI‑assisted tools

Tools

Airflow

Spark

AWS

Job description

Komodo Health, Inc. is seeking a Senior Data Engineer to design, build, and operate large-scale data pipelines powering the Healthcare Map. You will transform vast healthcare data into reliable, analysis-ready assets and collaborate across Data Product, Platform, and Engineering teams to deliver production-grade solutions.

You will contribute to system design, data quality, and observability while working in a hybrid US-based environment with potential remote opportunities.