Top Healthtech Data Engineering Jobs

Design and implement SQL transformations and datasets, manage data models in Databricks, optimize performance, and ensure compliance with data governance standards.

The ETL Architect is responsible for designing ETL architectures, development, and implementation of data models and warehousing solutions, with a focus on data quality and transformation logic.

The VP of Data will lead the data organization encompassing engineering and analytics, drive strategic insights, improve operational excellence, and integrate AI into workflows while ensuring data governance.

The Senior Director will lead global migration services, architecting data migration strategies for AI integration, and managing a team while ensuring quality delivery.

The Data Engineer will design and maintain data pipelines on Azure, manage ClickHouse for analytics, and ensure healthcare compliance while supporting ML integration.

Lead enterprise data function, oversee data architecture and engineering, ensure quality and compliance of healthcare data, manage teams, and develop scalable data solutions on Azure.

The ETL Engineer will design, develop, and optimize ETL pipelines using tools like Azure Data Factory and ClickHouse, ensuring performance and reliability while integrating data from various sources.

Manage the Analytics team, leading AI-driven data architecture, building scalable pipelines, establishing governance frameworks, and mentoring data engineers to enhance analytics capabilities.

The Data Architect designs data models, oversees database implementation, sets data standards, and leads data-related projects in a healthcare setting.

The Associate Director is responsible for implementing automation and AI workflows in biometrics, ensuring regulatory compliance, continuous improvement of standards, and collaboration across data management and analysis teams.

The Senior Data Engineer at HealthPartners will build, manage, and optimize data pipelines, collaborate with teams, design technology solutions, and ensure data reliability and quality while mentoring team members.

Design, build, and optimize ETL pipelines and data workflows. Collaborate with teams to translate requirements into data solutions, ensuring data quality and efficiency.