Top Healthtech Data & Analytics Jobs

As a Data Engineer, you will develop solutions for customer-centric technology, ensuring platform integration and managing data architecture. Responsibilities include building data processes, maintaining data integrity, and collaborating cross-functionally to meet business challenges.

The NetSuite Systems Engineer supports the NetSuite Administrator by providing technical support, managing NetSuite ERP, ensuring data quality, and facilitating user training and documentation.

The role involves overseeing statistical programming for oncology trials, providing guidance on regulatory submissions, managing cross-functional collaboration, and ensuring compliance with CDISC standards, while also leading programming teams and projects.

The Director of Data and Analytics will lead and grow the data function, overseeing team development, strategic execution, governance, and data integrity in a healthcare-focused environment.

This role develops foundational reporting and dashboards, collaborates with stakeholders to gather data requirements, and ensures data integrity while leveraging analytics and AI to support category strategy and execution.

The Global Pricing Solution Senior Specialist optimizes Viatris' global pricing system, ensuring compliance, effective pricing operations, and supporting stakeholders with system enhancements and training.

The Analyst, Partner Engagement will assist in project management, data analysis, and stakeholder collaboration to improve clinical outcomes in kidney care.

The Associate Director develops and executes pricing strategies, analyzing market dynamics, leading pricing initiatives, and ensuring compliance in the pharmaceutical industry.

Design, build, and maintain Scala-based ETL and streaming data pipelines, APIs, and data microservices in Azure. Optimize LLM fine-tuning and RAG workflows, support DevOps/CI-CD practices, document standards, mentor engineers, and manage data ingestion frameworks for analytics and partner integrations.

Owner of the semantic layer: build and maintain core data models and metrics, run dbt orchestration with CI/CD and testing, implement reverse ETL pipelines, and enforce PHI access controls to keep data HIPAA-compliant.