Top Healthtech Data & Analytics Jobs

Build and maintain the company-wide data foundation for FinOps; develop pipelines, dashboards, and operating scorecards; support stakeholders across commercial, finance, clinical ops, and operations; validate metrics with analytics engineers; transform messy datasets into actionable insights and adopt AI-powered workflows to improve efficiency.

The Principal Biostatistician leads biomarker analysis for clinical studies, develops evaluation plans, conducts data analyses, mentors staff, and ensures accurate statistical deliverables while collaborating across teams.

Own and build reliable analytics data products: define metrics, create and maintain dbt models, design dashboards for growth/finance/ops, improve data quality via testing and monitoring, and enable self-serve analytics for stakeholders.

Lead technology, data integration, platform operations, and technical validation for the HEDIS program. Manage ETL developers and support staff; oversee data feeds, production operations, data-quality controls, technical documentation, vendor coordination, audit support, and reporting. Support migration from Inovalon/Cotiviti to a future-state platform (Arcadia) and ensure HEDIS measurement, validation, and NCQA-related compliance.

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.

Lead enterprise analytics, integration, and application development strategy, overseeing data governance, architecture, middleware, and AI/ML solutions. Partner with business leaders to deliver analytics, integrations (SAP, Salesforce), and scalable applications, build high-performing teams, ensure compliance with QMS and regulated-environment requirements, and drive innovation through data-driven insights and automation.

Maintain and monitor Snowflake data warehouse and ingestion pipelines. Troubleshoot file/load/data quality issues, operate SFTP/drop-zone/file automation, support scheduled loads, build dbt models and tables, document runbooks, and serve as backup for core warehouse operations while collaborating with engineering and IT.

Lead and develop a team of data engineers while contributing hands-on to design, implement, and operate scalable, secure data pipelines. Partner with product, software, and architecture teams to deliver cloud-native data solutions, ensure production reliability, and drive engineering best practices and continuous improvement.

Lead design and scaling of ELT pipelines and analytics schemas on Snowflake. Build Looker views, CI/CD automation, and orchestration workflows (Prefect/Airflow). Ensure production reliability with monitoring (Datadog, Monte Carlo), partner with cross-functional teams, and provide technical leadership including code reviews, testing, and end-to-end ownership of data integrity and platform trustworthiness.

Data Engineer Interns will support analytics platform enhancements, data modeling, data exploration, pipeline maintenance, troubleshooting, optimization, documentation, and stakeholder collaboration. The role focuses on building data products, supporting AI-enabled analytics, and translating business needs into data requirements. Candidates should be enrolled in a quantitative degree program and have foundational knowledge of business intelligence, databases, data modeling, SQL, and data visualization.