# Staff Data Engineer

**Company:** [Komodo Health](https://hotfix.jobs/companies/komodo-health)
**Location:** Remote
**Role:** Data Engineering
**Salary:** $181k – $282k/yr
**Skills:** SQL, Python, Spark, Rust, C++, AI/ML, Cloud Data Platforms, Mpp Databases, Data Modeling
**Posted:** 2026-04-16

> Staff Data Engineer architects and delivers scalable data products from healthcare datasets, designs high-performance processing systems using SQL, Spark, Python, and AI workflows, and leads cross-functional initiatives for reliable data serving to customers and applications.

## Job Description

## 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 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.

## Requirements

- 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.

## Nice-to-Haves

- 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.

## Similar roles

- [Staff Data Engineer, Corporate Engineering](https://hotfix.jobs/jobs/1145710f-0512-426f-b3dc-11fae8c5c550) - Reddit - Remote - $180k – $252k/yr
- [Staff Data Engineer, Core Migrations](https://hotfix.jobs/jobs/6a217df9-0582-4916-a04b-ae102cfa5a33) - Machinify - Remote - $180k – $220k/yr
- [Staff Software Engineer, Batch Processing Platform](https://hotfix.jobs/jobs/9c400aa6-4baa-415a-9465-835083a27e99) - Pinterest - Remote - $177k – $365k/yr
- [Staff Data Engineer](https://hotfix.jobs/jobs/5ad59978-de00-44e6-bab9-07e1f9889b20) - NexHealth - San Francisco, CA - $177k – $226k/yr
- [Senior Staff Enterprise Architect, Data](https://hotfix.jobs/jobs/ffe430b2-4b1c-43db-b3b1-0e3750cf22c8) - MongoDB - Palo Alto, CA - $177k – $349k/yr

**Apply:** https://hotfix.jobs/jobs/2bec16ea-0906-42ff-b5d3-6e2a924385eb
**Canonical:** https://hotfix.jobs/jobs/2bec16ea-0906-42ff-b5d3-6e2a924385eb