REGISTRIEREN

Jobbörse

Finde Jobs in deiner Nähe – ob vor Ort, hybrid oder remote.
  • Ähnliche Jobs zu: Senior Data Engineer, Data Platform
XX
Senior Data Engineer, Data Foundations & AI PlatformKomodo Health • New York, New York, United States
Jetzt Bewerben
XX

Senior Data Engineer, Data Foundations & AI Platform

Komodo Health
  • US
    New York, New York, United States
  • US
    New York, New York, United States
Jetzt Bewerben

Über

We Breathe Life Into Data At Komodo Health, our mission is to reduce the global burden of disease. And we believe that smarter use of data is essential to this mission. That’s why we built the Healthcare Map — the industry’s largest, most complete, precise view of the U.S. healthcare system — by combining de-identified, real-world patient data with innovative algorithms and decades of clinical experience. The Healthcare Map serves as our foundation for a powerful suite of software applications, helping us answer healthcare’s most complex questions for our partners. Across the healthcare ecosystem, we’re helping our clients unlock critical insights to track detailed patient behaviors and treatment patterns, identify gaps in care, address unmet patient needs, and reduce the global burden of disease. As we pursue these goals, it remains essential to us that we stay grounded in our values: be awesome, seek growth, deliver “wow,” and enjoy the ride. At Komodo, you will be joining a team of ambitious, supportive Dragons with diverse backgrounds but a shared passion to deliver on our mission to reduce the burden of disease — and enjoy the journey along the way. The Opportunity at Komodo Health Join Komodo Health's Data Foundations 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 be responsible for designing, implementing, and scaling the foundational data systems and pipelines that power Komodo Health’s platform and analytics products. This role owns the end-to-end data processing lifecycle—from ingestion and modeling to serving—on a massive scale, utilizing cloud infrastructure and advanced distributed computing techniques. This platform also serves as the foundation for AI/ML and agentic applications across Komodo Health. You will set technical direction, ensure data quality, and be a technical leader in tackling the most complex data problems in healthcare. 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. Healthcare Data Innovation: Develop deep domain expertise and contribute novel approaches to challenges such as patient journey mapping and identity resolution. Cross-Functional Delivery: Partner with Data Product and Engineering teams to ship scalable, production-grade data solutions. Technical Leadership: Raise the bar across the team through mentorship, design reviews, and engineering best practices. Key Responsibilities Design and implement high-performance data processing and serving patterns across large-scale healthcare datasets using Spark, Python, Rust, and SQL, supporting both analytics and AI/ML workloads. Lead complex cross-functional initiatives, balancing trade-offs across scalability, reliability, performance, cost, and delivery speed. Build and maintain robust data quality, validation, observability, lineage, monitoring, and alerting frameworks. Architect scalable Healthcare Map data products that power APIs, analytics, internal tooling, and customer-facing applications. Partner with Product, Data Science, and Platform teams to translate healthcare use cases into scalable technical solutions. Drive engineering excellence across system design, code quality, testing, documentation, and CI/CD practices. Mentor engineers through design reviews, technical coaching, and architectural guidance. Enable AI/ML and agentic applications by delivering high-quality, feature-ready datasets, curated data products, and reliable serving layers for training, inference, and evaluation. What you bring to Komodo Health: AI & ML Enablement: Experience designing data workflows, feature pipelines, or infrastructure that specifically supports AI/ML training, inference, experimentation, and monitoring. Data Product Engineering: Proven experience building large-scale, production-grade data products and analytical systems. Modern Data Systems: Strong expertise in SQL, distributed processing frameworks (e.g. Spark), cloud data platforms, and high-scale compute systems using Python and/or Rust. Architecture & Systems Design: Demonstrated ability to design scalable data models, platform components, and distributed system architectures. Analytical Rigor: Strong statistical and analytical skills; able to validate data quality and product outcomes through rigorous analysis. Technical Communication: Clear communicator who can explain technical decisions, trade-offs, and risks to engineers, product partners, and leadership. AI-Augmented Engineering Expectations: You will be expected to leverage AI-Augmented Engineering tools (such as ChatGPT, Gemini, or Claude) to significantly improve productivity. This includes using AI for generating and refining complex code snippets, accelerating documentation creation, automating test case generation, performing technical deep dives to understand new concepts, and rapidly assessing design trade-offs and risks in architectural planning. This includes using AI not only for productivity, but also for accelerating system design, debugging, and architectural decision-making. Additional skills and experience we’d prioritize (nice to have)… Healthcare Data Experience: Direct experience with claims, clinical, RWE, provider, patient, or life sciences data, including familiarity with coding systems (ICD-10, CPT, NDC, NPI). Data Product Delivery: Experience building and operating data products specifically designed for external consumption via customers, APIs, or serving layers. High-Scale Data Architecture: Proven experience in optimizing systems for performance, cost efficiency, versioning, and large-volume data productization. Applied AI / Agentic Workflows: Experience applying AI/agentic workflows to engineering, data quality, or delivery processes. Fast-Growth Execution: Experience successfully operating in high-growth or ambiguous environments where leaders must adeptly balance architecture, delivery speed, and quality. Open to US remote, OR SF/NYC hybrid #LIRemote 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: $176,000 — $207,000 USD All Other US Locations: $153,000 — $180,000 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've 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. Join us in shaping the future of healthcare intelligence.
Where You’ll Work 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. By submitting your application, you acknowledge that you have read and understand Komodo Health’s Privacy Notice for Employees and Contractors . This notice explains how we collect, use, and retain applicant data.
#J-18808-Ljbffr
  • New York, New York, United States

Sprachkenntnisse

  • English
Hinweis für Nutzer

Dieses Stellenangebot stammt von einer Partnerplattform von TieTalent. Klick auf „Jetzt Bewerben”, um deine Bewerbung direkt auf deren Website einzureichen.