Data Platform Engineer

Join Our Team as Data Platform Engineer! 🚀

Urologic Health | MedTech | Cloud Data Pipeline & ML, Location: Or Yehuda / Hybrid

We’re a young, innovative medical startup building a revolutionary non-invasive sensing platform that transforms complex real-world signals into meaningful clinical insights. Our technology integrates advanced sensing and data analytics to enable better diagnostics and monitoring of urological conditions. 

If you're excited about building scalable cloud data pipelines and want to work on technology that impacts millions of patients, we’d love to hear from you.

Role Overview

We are seeking an experienced hands-on engineer to design and build a scalable cloud-based data platform that processes data from multiple sensors, runs analytics, machine learning models and generates clinical reports.

You will be responsible for building the end-to-end data pipeline, including ingestion, processing, ML inference, storage, monitoring, and model lifecycle management. The ideal candidate combines data engineering, cloud infrastructure, and ML operationalization (MLOps) experience.

What you'll do

• Build a cloud-based data pipeline for sensor data processing
• Implement Python processing services and analytics workflows
• Deploy and run machine learning models in production
• Design scalable storage for raw data, processed data, and reports
• Implement monitoring, logging, and observability
• Build infrastructure for both model retraining and users database.

Required Qualifications

• 3+ years experience in data engineering, backend engineering, or ML infrastructure 
• Strong Python programming skills
• Experience in building data pipelines in cloud environment
• Experience with processing pipelines for streaming or event-driven data
• Familiarity with deploying and running ML models in production
• Experience with monitoring, logging, and observability tools
• Experience designing scalable data storage systems

Preferred Qualifications

• Experience in health tech / medical device /regulated environments (key advantage)
• Experience with sensor data or time-series data
• Experience with MLOps frameworks and model lifecycle management
• Experience working in early-stage or small engineering teams

What Makes This Role Unique

• Opportunity to design the entire data and ML infrastructure from the ground up
• Work on cutting-edge medical technology
• Hybrid work mode with flexible hours - we care about impact, not clock-watching.
• A small team where your work matters from day one
• Startup energy with serious technical depth

📩 Interested?  

Send your CV (and optionally GitHub) to noamo@urologic.health  

with the subject: Data Platform Engineer Application.