Top Healthtech Data & Analytics Jobs

Analyze healthcare claims, authorization, eligibility, and clinical data to build customer-facing dashboards, answer complex utilization and cost questions, support ROI analyses, investigate data quality issues, and define consistent metrics for the analytics platform. Present findings to health plan stakeholders and collaborate with Product, Engineering, Data Science, Clinical Operations, and Customer Success.

Leads the enterprise Business Intelligence Systems team and oversees global implementation, governance, maintenance, and improvement of BI, analytics, AI, data management, and Microsoft Power Platform solutions. Manages team personnel, establishes standards, ensures data quality and security, supports self-service analytics, translates business needs into scalable solutions, and drives training, adoption, documentation, project delivery, and continuous process improvement.

Perform advanced workforce and talent analyses, build self-service BI products and dashboards, generate and present insights to Talent and Executive leadership, collaborate with Finance and Human Capital for workforce planning, and partner with teams to identify opportunities for deeper analytics and process automation.

Develops and maintains production, ad hoc, compliance, and forecasting reports for a health insurance division. Analyzes reporting needs, retrieves and validates data, designs reporting processes, supports statistical analysis, manages reporting requests, trains staff, and serves as a technical resource. The role requires health insurance or financial analytics experience, programming applications, and knowledge of health plan financial concepts.

Designs and delivers scalable data pipelines, models, repositories, dashboards, and reporting solutions. Partners with business and technology stakeholders to translate requirements into technical solutions, supports ETL/ELT processes, ensures data quality and performance, leads projects, mentors team members, and promotes automation and continuous improvement across Guardian Pharmacy’s data platform.

Designs, builds, and maintains reliable data pipelines and platforms in AWS environments. Develops ETL/ELT workflows, data models, integrations, quality checks, monitoring, and infrastructure for analytics, applications, and AI initiatives. Collaborates with data scientists, analysts, and software engineers while documenting solutions and troubleshooting production systems. The role is remote within the continental United States and emphasizes Python, SQL, orchestration, relational databases, and cloud data infrastructure.

Leads U.S. execution of an enterprise data governance operating model, including ownership, stewardship, classification, data quality, governance forums, and adoption. Establishes domain governance, facilitates working groups, translates policy into business practices, manages exceptions and risks, trains stakeholders, and supports data governance for acquisitions. Requires strong cross-functional influence, stakeholder communication, and extensive data governance experience.

Analyzes sales and distribution channel performance, develops Power BI dashboards and executive reports, evaluates sales incentive plans, and provides data-driven recommendations. Partners with Sales, Finance, Human Resources, and product stakeholders to define metrics, monitor trends, assess compensation outcomes, and improve strategic decision-making. Ensures accurate, accessible reporting and translates complex data into actionable business insights.

Leads U.S. execution of the enterprise data governance model, including ownership, stewardship, classification, data quality, governance forums, and standards adoption. Facilitates cross-functional domain working groups, drives training and communications, manages exceptions and risks, strengthens data governance networks, and supports data governance for acquisitions. Requires extensive data governance experience, stakeholder communication, and the ability to influence without direct authority.

Designs and maintains a scalable data platform supporting analytics, machine learning, and AI workloads. Builds tooling for reliable data pipelines, semantic layers, data agents, LLM applications, and evaluation systems. Ensures data quality, availability, observability, and reliability while establishing modeling, testing, and platform best practices. Collaborates with Data Science and Product Engineering, leads solutions from design through implementation, and contributes individually in a fast-paced startup environment.