Top Healthtech Data & Analytics Jobs

Develops scalable data models, dashboards, reports, data pipelines, and reporting workflows using Power BI and SQL. Ensures data integrity, supports performance measurement, conducts advanced analysis, and translates program requirements into actionable insights. Supervises data analysts, supports agency-wide performance frameworks, integrates disparate data sources, maintains data structures, and partners with IT on data governance, interoperability, and quality improvement.

Designs, develops, maintains, and optimizes complex data systems, SQL databases, ETL processes, data warehouses, reports, and .NET applications supporting pharmacy benefit management. Responsibilities include database performance tuning, troubleshooting pharmacy claims processes, developing scalable solutions, documenting technical designs, participating in Agile ceremonies, collaborating with stakeholders, mentoring teammates, and ensuring healthcare data compliance.

Build and optimize Hipp’s analytics data platform, including production data pipelines, warehouses, schemas, dashboards, reports, and data models. Write complex SQL, monitor data quality, perform product and operational analysis, and translate business needs into technical solutions. Collaborate with product managers and data scientists to support AI and ML initiatives, deliver reliable insights, and inform product strategy.

Builds Power BI dashboards, semantic models, DAX measures, Power Query transformations, and SQL components for marketing analytics. Develops and evaluates AI agents using governed data, supports QA and release practices, monitors data refreshes and defects, and participates in stakeholder workshops, demonstrations, and user-acceptance testing. The role works under technical leadership while developing analytics engineering expertise.

The Product Analyst will manage the product experience, consult clients, collaborate with internal teams, and guide new features in biotech and pharma contexts.

Design, implement, and optimize large-scale data processing on Databricks and Spark. Build ETL pipelines, integrate data across AWS services (Redshift, RDS), orchestrate workflows with Airflow, and ensure data warehousing and engineering best practices. Lead and mentor development teams and collaborate with cross-functional stakeholders to drive data strategy and execution.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

Own the end-to-end architecture and roadmap for MyFitnessPal’s product data stack. Coordinate data engineering, business intelligence, product analytics, and backend teams; establish data movement and standardization practices; lead tool evaluations and platform migrations; implement governance, PII handling, deletion workflows, access controls, and cost optimization; and document architecture standards across the organization.

Leads PBM data integration delivery across claims, eligibility, accumulator, and encounter systems. Profiles and validates data, writes advanced SQL, resolves reconciliation discrepancies, investigates production issues, and partners with engineering on scalable healthcare integration architecture. Owns timelines, risks, vendor dependencies, testing, UAT, migration, rollback planning, executive reporting, and post-deployment support. Requires deep PBM claims-processing expertise, data architecture experience, and hands-on knowledge of ETL, secure file transfer, job scheduling, and healthcare data standards.

The Research Analyst analyzes CRI-funded research and grant data to track outcomes, evaluate impact, identify trends, and support portfolio reporting. Responsibilities include cleaning and connecting data from reports, publications, surveys, databases, and SmartSimple; developing metrics, dashboards, visualizations, case studies, and analytical summaries; validating data quality; documenting methods; and communicating insights to scientific and cross-functional teams.