Software Engineer, Data & Analytics Platform

Role overview

Build and scale the data and analytics platform that shows how clinical AI products perform across health systems. You’ll create reliable data infrastructure and practical tools for teams to investigate cases, monitor results, and make informed product decisions. The role works across engineering, data science, clinical, product, and client-facing teams.

Responsibilities

- Develop secure, scalable data lakehouse and warehouse foundations for analytics and machine learning. - Improve data models, orchestration, data quality, and system scalability as products and customers grow. - Build self-service tools and frameworks, including LLM-enabled automation, so teams can explore data without writing queries. - Create pipelines and models that track product KPIs and clinical AI performance across customers and modules. - Collaborate across teams to define meaningful measures of success and maintain trustworthy supporting data.

Requirements

- Bachelor’s degree in computer science or a related technical field. - At least five years building secure, scalable cloud data or analytics infrastructure for live products; cloud experience, preferably AWS. - Proficiency in Python and SQL. - Strong knowledge of modern data warehouses, transformation frameworks, workflow orchestration, and business intelligence tools. - Experience applying LLMs in distributed data processing or analytics systems. - Strong communication and cross-functional collaboration skills, with the ability to translate varied requirements into robust technical solutions.

Nice to have

Experience securely handling sensitive personal or health information, building analytics for clinical or health data, or working through ambiguity in a startup environment.