Staff Data Engineer

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.

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; 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 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; Raise the bar for system design, code quality, documentation, testing, CI/CD, and operational readiness; Mentor engineers through design reviews, technical deep dives, pairing, and architectural guidance

Requirements

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

Nice to have

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

Benefits

Comprehensive health, dental, and vision insurance; Flexible time off and holidays; 401(k) with company match; Disability insurance and life insurance; Leaves of absence; Performance-based bonuses; Equity awards