Software Engineer, Data & Analytics Platform

Description

The company is a fast-growing startup that uses real-time clinical data to help physicians, nurses, and care team members act earlier and improve patient outcomes.

The team is building a data and analytics platform that shows the company and its clients how its clinical AI products perform in every hospital served. You will help shape key technical decisions and build the data infrastructure that both the company and its clients depend on.

The company is made up of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders. It is funded by venture investors and has been recognised by Forbes, the World Economic Forum, Time, and BioTech AI awards. A recent Nature Medicine publication links its products to lives saved.

Responsibilities

• Work with engineers, data scientists, clinicians, product managers, and client success partners to turn complex clinical data into reliable, actionable insights.
• Design pipelines and data models, build tools that help teams monitor product performance and investigate clinical cases, and improve the platform as new products and health systems are added.
• Give the company a clear view of how its AI performs, informing how it grows its clinical AI offerings and supports clients.
• Build the data lakehouse and warehouse with secure, scalable pipelines that feed analytics and machine learning. As products and the client base grow, improve data modelling, orchestration, data quality, and scalability.
• Create tools and frameworks that let Clinical, Client Success, and Product teams get answers from data without writing queries, including reviewing and flagging clinical cases and spotting trends and opportunities. Use LLMs and automation to make this possible.
• Design pipelines and data models that automatically track KPIs and model performance for every client and clinical module, working with real-time EHR data that is messy and varied.
• Work with Client Success, Clinical, Product, Data Science, and Engineering to define how product success is measured and make sure the data behind those measures can be trusted.

Requirements

• Bachelor's degree in Computer Science or another relevant technical discipline.
• 5+ years building scalable, secure data or analytics infrastructure on a cloud platform, preferably AWS, for live products and customers.
• Strong Python and SQL skills.
• Deep knowledge of modern data and analytics tools, such as cloud data warehouses, transformation frameworks like dbt, workflow orchestration tools, and BI tools like Tableau or QuickSight. You know how to integrate them with existing infrastructure to add capability.
• Experience using LLMs within distributed data processing and analytics systems.
• Excellent communication skills and a proven record of working across data science, product, and clinical teams to turn requirements into robust technical solutions.
• Preferred: experience handling sensitive PHI and PII data securely.
• Preferred: experience building analytics technology for clinical or health data.
• Preferred: experience working through ambiguity and uncertainty in a startup.

Conditions

This policy covers all employment terms, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leave, compensation, and training.