Top Healthtech Data & Analytics Jobs

The Data Engineer will build and maintain data platforms, deploy pipelines, monitor transformations, and collaborate with Data Scientists and DevOps.

The Commercial Analytics Analyst collaborates with Sales and other stakeholders to deliver analytics solutions, insights, and recommendations driving revenue growth and sales effectiveness. Responsibilities include creating dashboards, analyzing data, and leveraging AI for improvements.

As a Senior Data Engineer at Nimble, you will own the data platform, build and optimize data pipelines, ensure data compliance, and mentor team members, while collaborating across departments to enhance data accessibility and usage.

The Data Solutions Architect at MANSCAPED will manage the enterprise data architecture, ensure security and scalability, and support BI reporting and advanced analytics.

Support VHA specialty care programs with enterprise data management, BI, reporting, and automation. Build Power BI dashboards, automate data acquisition with Microsoft Power Platform, integrate solutions with VA systems, analyze healthcare/financial data, and produce executive reporting, documentation, and training to support decision-making and performance improvement.

Lead and scale the data engineering function: design and maintain Azure-based data warehouse and high-performance ETL pipelines, ensure data quality and governance, mentor the team, collaborate with stakeholders, and drive data strategy and innovation.

Design, implement, and maintain enterprise data warehouse systems and ETL pipelines. Lead data modeling, performance tuning, data integration, and testing. Produce documentation, metadata, and ad-hoc queries while troubleshooting data issues and ensuring data quality, usability, and alignment with standards and business needs.

Design, build, and maintain dbt data models and scalable ELT pipelines; optimize performance-aware SQL on Snowflake; ensure observability, testing, and CI/CD; partner with product and engineering teams to meet analytic needs, mentor engineers, document business logic, and troubleshoot ingestion, transformation, and warehouse issues.

Build and maintain reliable, observable data pipelines and a dbt-based transformation layer. Create analytics data models for in-product client reporting and internal dashboards, enforce data quality checks, and collaborate with Product and commercial teams to support analytics needs.

Design, build, and operate a scalable, secure data platform. Architect end-to-end data pipelines, manage Snowflake performance and costs, implement CI/CD and observability, ensure data governance and HIPAA alignment, integrate diverse sources, mentor teammates, and support analytics and business users.