Data Engineer

ZimZee Recruiting is looking for a Data Engineer to join our medical device client in Lehi focused on building reliable data infrastructure and supporting machine learning workflows in production. This role is ideal for someone who enjoys solving complex technical challenges, building scalable systems, and taking ownership of projects from design through deployment. The engineer should have strong Kubernetes experience, who writes clean code, improves existing systems, and collaborates effectively to deliver real business value.

Skills and Requirements

• 2 - 4+ years of professional experience as a Data Engineer, Software Engineer, or similar technical role.
• Strong Python programming skills with the ability to write clean, maintainable, and production-ready code.
• Advanced understanding of mathematical principles with the ability to translate mathematical models into data transformation pipelines.
• Experience designing, building, and optimizing batch and streaming data pipelines.
• Strong SQL skills, including query optimization and data modeling.
• Experience with workflow orchestration tools such as Airflow, Prefect, Dagster, or similar DAG-based scheduling platforms.
• Hands-on experience with Kubernetes and Docker for deploying and managing production workloads.
• Familiarity with deploying, operationalizing, and monitoring machine learning models in production environments.

Key Responsibilities

• Design, develop, and maintain scalable batch and streaming data pipelines that support analytics and machine learning applications.
• Develop robust Python-based data processing solutions and contribute C++ code when appropriate.
• Design, optimize, and maintain SQL queries and data models to ensure efficient and reliable data processing.
• Build, manage, and optimize workflow orchestration using DAG-based scheduling frameworks.
• Support the deployment, data preparation, integration, and basic monitoring of machine learning models in production.
• Deploy and maintain production workloads using Docker and Kubernetes while ensuring system reliability and performance.