Staff Data Engineer

Komodohealth; United States; Hybrid; USD 181,000 - 282,000; Full time

Benefits offered by this job

Comprehensive health insurance

Flexible time off

401(k) with company match

Disability and life insurance

Job summary

Komodo Health is looking for a Staff Data Engineer to architect and deliver innovative healthcare data products. This role is crucial in transforming vast amounts of data into meaningful insights and requires expertise in modern data systems.

The position offers a hybrid work model with the potential to earn between $208,000 and $282,000 annually in major cities, with opportunities for performance bonuses and comprehensive benefits.

Qualifications

• Extensive experience building production-grade, large-scale data products.
• Strong technical depth across SQL, distributed data processing, cloud data platforms.
• Demonstrated ability to design data models and system architectures.

Responsibilities

• Architect, build, and deliver scalable healthcare data products.
• Design and implement high-performance data processing across large-scale datasets.
• Build data products that are easy to consume through APIs and other delivery mechanisms.

Skills

Data Product Engineering Expertise

Modern Data Systems Depth

Architecture & Systems Design

Healthcare Data Product Judgment

AI & ML Enablement

Analytical & Statistical Rigor

Technical Communication

AI-Augmented Engineering

Tools

SQL

Python

Spark

Rust

C++

Job description

The Opportunity at Komodo Health

Team: Data Foundations owns the core data products that power Komodo’s Healthcare Map. We design and deliver the foundational data assets, models, and serving capabilities that make healthcare data usable, performant, and trustworthy for customers and internal product teams. Our work reaches customers directly and also powers consuming applications through APIs, analytics layers, and other data delivery surfaces.

Mission

Mission: This role exists to architect and deliver the foundational data products and serving capabilities that turn complex healthcare data into trusted, production-ready assets for customers and applications. As a Staff-level IC, you will set technical direction across data modeling, productization, analytics enablement, and scalable delivery patterns, partnering with Product, Data Science, and consuming application teams to make Healthcare Map data usable at enterprise scale.

Role Overview

Komodo Health leverages the latest engineering technology to tackle healthcare’s biggest challenges by transforming extraordinary amounts of data into meaningful insights. As a Staff Data Engineer, you will drive the development of state‑of‑the‑art foundational products that unlock the potential of our Healthcare Map, fostering a culture of technical excellence and transparency across the organization.

First 12 months accomplishments

• Architectural Advancement: Managed and delivered high‑impact projects that introduced new technical and data services to market, significantly improving pipeline performance.
• Innovation in Healthcare Data: Developed a deep understanding of domain‑specific challenges and introduced innovative algorithms that address complex patient journey mapping.
• Collaborative Roadmap Delivery: Partnered across Data Product and Engineering to define technical requirements and deliver scalable, production‑grade solutions that meet business needs.
• Platform Hardening: Built and hardened core Data Foundations components, measurable through improved reliability, observability, and cost‑efficiency of our Healthcare Map products.
• Technical Multiplication: Mentored and up‑leveled the engineering team, raising the bar for code quality and system design through coaching and rigorous design reviews.

Essential Job Duties

• Data Product Development & Delivery: Architect, build, and deliver scalable Healthcare Map data products that power direct customer use cases, APIs, analytics surfaces, serving layers, and internal applications.
• Scalable Data Systems: Design and implement high‑performance data processing and serving patterns across large‑scale healthcare datasets, using the right tools for the problem across SQL, Python, Spark, Rust, C++, and emerging AI‑enabled engineering workflows.
• Foundational Data Models: Create shared data models, productized datasets, reusable libraries, and technical standards that become the foundation for downstream product, analytics, and application teams.
• Serving & Consumption Enablement: Build data products that are easy to consume through APIs, serving layers, exports, analytics environments, and customer‑facing delivery mechanisms.
• Cross‑Functional Product Delivery: Partner with Product, Data Science, Quality, Platform, and application teams to translate complex healthcare use cases into production‑grade technical designs and execution plans.
• Technical Leadership: Lead complex, multi‑quarter initiatives, making clear trade‑offs across performance, scalability, maintainability, cost, reliability, and time‑to‑market.
• Quality, Observability & Trust: Define and implement data quality checks, validation frameworks, observability, lineage, monitoring, and alerting to ensure Healthcare Map products are accurate, explainable, and reliable.
• Engineering Excellence: Raise the bar for system design, code quality, documentation, testing, CI/CD, and operational readiness across the team.
• Engineering Leverage: Mentor engineers through design reviews, technical deep dives, pairing, and architectural guidance, helping the team make better decisions at scale.

Required Qualifications

• Data Product Engineering Expertise: Extensive experience building production‑grade, large‑scale data products, services, and analytical systems that serve real customer and business use cases.
• Modern Data Systems Depth: Strong technical depth across SQL, distributed data processing, cloud data platforms, MPP databases, and high‑scale compute frameworks such as Spark, Python, Rust, C++, or equivalent technologies.
• Architecture & Systems Design: Demonstrated ability to design data models, serving patterns, platform components, and system architectures for complex, high‑volume data environments.
• Healthcare Data Product Judgment: Ability to reason through data quality, identity, longitudinal patient journeys, claims or clinical data complexity, and downstream consumption needs.
• AI & ML Enablement: Experience designing data workflows, feature pipelines, evaluation datasets, or infrastructure that supports AI/ML training, inference, experimentation, and monitoring.
• Analytical & Statistical Rigor: Strong ability to use data analysis, statistical reasoning, hypothesis testing, and experimental design to validate product quality and business impact.
• Technical Communication: Ability to explain technical decisions, trade‑offs, risks, and delivery status clearly to engineers, product partners, data scientists, and senior stakeholders.
• AI-Augmented Engineering: Ability to use AI tools such as ChatGPT, Gemini, Cursor, Claude, or similar systems to improve engineering productivity, design quality, testing, documentation, and decision‑making.

Preferred Qualifications

• Healthcare Data Experience: Experience with claims, clinical, RWE, provider, patient, or life sciences data, including familiarity with coding systems such as ICD‑10, CPT, NDC, RxNorm, NPI, or taxonomy data.
• Data Product Delivery: Experience building and operating data products that are consumed by customers, analytics users, APIs, applications, or serving layers.
• High‑Scale Data Architecture: Experience designing systems for large‑volume data processing, productization, versioning, delivery, performance optimization, and cost efficiency.
• Applied AI / Agentic Workflows: Experience using, designing, or integrating AI‑enabled workflows to improve engineering productivity, data quality, extraction, curation, testing, or product delivery.
• Fast‑Growth Execution: Experience operating in high‑growth or ambiguous environments where technical leaders must balance architecture, delivery, quality, and speed.

Compensation

The pay range for each job posting reflects a minimum and maximum range of annual base pay that we reasonably expect to pay for this position within the US. We carefully consider multiple business‑related factors when determining compensation, including job‑related skills, work experience, geographic work location, relevant training and certifications, business needs and market demands.

The starting annual base pay for this role is listed below. This position may be eligible for performance‑based bonuses as determined in the Company’s sole discretion and in accordance with a written agreement or plan. This role may also be eligible for equity awards. In addition, this role is eligible for benefits including, but not limited to, comprehensive health, dental, and vision insurance; flexible time off and holidays; 401(k) with company match; disability insurance and life insurance; and leaves of absence in accordance with applicable state and local laws and regulations and company policy.

San Francisco Bay Area and New York City: $208,000 – $282,000 USD

All Other US Locations: $181,000 – $245,000 USD

Komodo’s AI Standard

At Komodo, we’re not just witnessing the AI revolution – we’re leading it. This is a pivotal moment in time, where being first to market with AI transforms industries and sets the bar. We have already established industry leadership in leveraging AI to revolutionize healthcare, and we expect every team member to contribute. AI here isn’t optional; it’s foundational. We expect you to integrate AI into your daily work – from summarizing documents to automating workflows and uncovering insights. This isn’t just about efficiency; it’s about making every moment more meaningful, building on trust in AI, and driving our collective success.

Location and Work Environment

Komodo Health has a hybrid work model with hubs in San Francisco, New York City, and Chicago. Roles vary – some can be performed from anywhere in the country, others are scoped to a specific region, and some are based near one of our hubs. For hub‑based Dragons, we’re building intentional in‑office rhythms alongside the flexibility that’s core to how we work. Whatever your setup, expectations will always be clear before you join.

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.

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