Teams at Egen

Designs and builds data ingestion, feature engineering, analytics, and machine learning pipelines using healthcare and other structured or unstructured data. Develops, tunes, deploys, monitors, and documents predictive models and enterprise data products. Collaborates with data scientists, engineers, product managers, and stakeholders while ensuring data quality, reliability, and production engineering standards.

Build and maintain full-stack applications that deliver AI/ML insights through backend services, REST APIs, containerized microservices, and high-performance front-end interfaces. Responsibilities include cloud-native development on Google Cloud or Azure, database management, testing, CI/CD automation, security, troubleshooting, and Agile collaboration.

Leads the architecture, design, and implementation of scalable GCP and Databricks data lakehouse platforms. Designs real-time and batch pipelines, data models, governance, cataloging, security, and performance optimization. Advises clients, translates business requirements into technical solutions, leads project teams, mentors engineers, reviews architectures, and balances strategic planning with hands-on proof-of-concept and troubleshooting work.