Senior Data Engineer

Komodohealth; United States; On-site; USD 180,000 - 238,000; Full time

Benefits offered by this job

Comprehensive health, dental, and vision insurance

Flexible time off

401(k) with company match

Disability and life insurance

Job summary

Komodo Health is seeking a Senior Data Engineer to join its Knowledge & Information team. In this role, you will design, build, and improve large-scale data pipelines that power the Healthcare Map and analytics products.

The ideal candidate will have strong experience with Python and SQL, along with a solid understanding of AWS and data reliability principles. The position offers competitive compensation ranging from $180,000 to $238,000, depending on location, along with benefits including health insurance and 401(k) matching.

Qualifications

• Strong hands-on experience with production-grade data pipelines at scale.
• Advanced skills in Python and SQL.
• Experience with orchestration tools and distributed processing frameworks.

Responsibilities

• Build and optimize large-scale production data pipelines.
• Develop data acquisition systems for unstructured data sources.
• Transform healthcare datasets into usable data products.

Skills

Python

SQL

Data Pipeline Development

AWS

Airflow

Spark

Job description

Opportunity at Komodo Health

Join Komodo Health's Knowledge & Information team and play a critical role in shaping the core data products that fuel our Healthcare Map. This role is essential for transforming massive, complex healthcare datasets into performant, trustworthy, and usable data assets that directly power both customer-facing applications and internal product innovation. By building and scaling our foundational data systems, you will directly enable the transparency and efficiency required to drive better health outcomes across the industry.

Mission

The Senior Data Engineer 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. This is a hands‑on engineering role focused on processing complex healthcare data at scale, improving reliability and performance, and contributing to the technical direction of core data systems.

Looking back on your first 12 months at Komodo Health, you will have…

• Architectural Advancement: Deliver high-impact technical initiatives that improve pipeline performance, scalability, and system efficiency.
• Platform Hardening: Improve the reliability, observability, and cost-efficiency of core Data Foundations systems.
• Cross-Functional Delivery: Partner with Data Product and Engineering teams to ship scalable, production-grade data solutions.

You will accomplish these outcomes through the following responsibilities…

• Build, operate, and optimize large-scale production data pipelines using Python, SQL, Airflow, cloud infrastructure, and distributed processing frameworks — including robust data quality checks, validation, lineage, observability, monitoring, and alerting.
• Design and scale agentic data acquisition and extraction systems for complex, unstructured public data sources; develop LLM-powered Human-in-the-Loop pipelines for data extraction and curation.
• Transform healthcare claims, EHR, non-claims-based, and reference datasets into trusted, performant Healthcare Map data products and serving‑ready data assets.
• Contribute to system design, architecture, code quality, testing, documentation, CI/CD, and rotational production support — including debugging 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 that enable downstream analytics, product, and AI/ML use cases.

What you bring to Komodo Health:

• Strong hands‑on experience building, operating, and debugging production‑grade data pipelines at scale in AWS, with sharp instincts for data quality, reliability, root‑cause analysis, and production troubleshooting.
• Advanced Python and SQL skills; experience with Airflow or similar orchestration tools and Spark or comparable distributed processing frameworks.
• Ability to communicate technical trade‑offs clearly and collaborate across engineering, product, and data teams.
• Comfort using AI-assisted engineering tools for productivity, debugging, documentation, and technical exploration.

AI-Augmented Engineering Expectations

• You will be expected to leverage AI-augmented engineering tools, such as ChatGPT, Gemini, or Claude, to improve productivity and technical decision‑making. This may include using AI to generate and refine code, accelerate documentation, automate test case creation, debug complex issues, explore unfamiliar technical concepts, and assess architectural trade‑offs and risks.

Additional skills and experience we’d prioritize (nice to have)…

• Healthcare data experience is a plus, but not required.
• 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.
• Proven success in high-growth or ambiguous environments that require balancing architecture, speed, and quality.

Compensation

San Francisco Bay Area and New York City: $207,000 – $238,000 USD per year. All other US locations: $180,000 – $207,000 USD per year. This role may be eligible for performance‑based bonuses and equity awards. Benefits include comprehensive health, dental, and vision insurance; flexible time off and holidays; 401(k) with company match; disability insurance and life insurance; leaves of absence in accordance with applicable state and local laws and regulations and company policy.

Equal Opportunity Statement

Komodo Health provides equal employment opportunities to all applicants and employees. We prohibit discrimination and harassment of any type with regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.