[Remote] Staff Data Engineer

Note: The job is a remote job and is open to candidates in USA. Komodo Health is dedicated to reducing the global burden of disease through smarter use of data. The Staff Data Engineer will architect and deliver foundational data products and capabilities that turn complex healthcare data into trusted, production-ready assets for customers and applications.

Responsibilities

• Architect, build, and deliver scalable Healthcare Map data products that power direct customer use cases, APIs, analytics surfaces, serving layers, and internal applications
• 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
• Create shared data models, productized datasets, reusable libraries, and technical standards that become the foundation for downstream product, analytics, and application teams
• Build data products that are easy to consume through APIs, serving layers, exports, analytics environments, and customer-facing delivery mechanisms
• Partner with Product, Data Science, Quality, Platform, and application teams to translate complex healthcare use cases into production-grade technical designs and execution plans
• Lead complex, multi-quarter initiatives, making clear trade-offs across performance, scalability, maintainability, cost, reliability, and time-to-market
• Define and implement data quality checks, validation frameworks, observability, lineage, monitoring, and alerting to ensure Healthcare Map products are accurate, explainable, and reliable
• Raise the bar for system design, code quality, documentation, testing, CI/CD, and operational readiness across the team
• Mentor engineers through design reviews, technical deep dives, pairing, and architectural guidance, helping the team make better decisions at scale

Skills

• Extensive experience building production-grade, large-scale data products, services, and analytical systems that serve real customer and business use cases
• 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
• Demonstrated ability to design data models, serving patterns, platform components, and system architectures for complex, high-volume data environments
• Ability to reason through data quality, identity, longitudinal patient journeys, claims or clinical data complexity, and downstream consumption needs
• Experience designing data workflows, feature pipelines, evaluation datasets, or infrastructure that supports AI/ML training, inference, experimentation, and monitoring
• Strong ability to use data analysis, statistical reasoning, hypothesis testing, and experimental design to validate product quality and business impact
• Ability to explain technical decisions, trade-offs, risks, and delivery status clearly to engineers, product partners, data scientists, and senior stakeholders
• 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
• 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
• Experience building and operating data products that are consumed by customers, analytics users, APIs, applications, or serving layers
• Experience designing systems for large-volume data processing, productization, versioning, delivery, performance optimization, and cost efficiency
• Experience using, designing, or integrating AI-enabled workflows to improve engineering productivity, data quality, extraction, curation, testing, or product delivery
• Experience operating in high-growth or ambiguous environments where technical leaders must balance architecture, delivery, quality, and speed

Benefits

• Performance-based bonuses as determined in the Company’s sole discretion and in accordance with a written agreement or plan
• Equity awards
• 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
• Hybrid work model with hubs in San Francisco, New York City, and Chicago

Company Overview

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