Top Healthtech Data & Analytics Jobs

Analyze large datasets using SQL and Python, build dashboards and recurring reports, identify trends and data-quality issues, and translate ambiguous business questions into actionable insights. The role partners with product, customer success, and engineering teams, documents metrics and methodologies, and presents findings to technical and non-technical stakeholders. Healthcare data, supply chain analytics, modern analytics engineering, and BI visualization experience are advantageous.

Designs, develops, tests, and maintains scalable data systems, SQL/ETL procedures, reporting processes, and .NET applications supporting pharmacy benefit management. Responsibilities include database performance optimization, query tuning, troubleshooting pharmacy claims and NCPDP submissions, technical design, stakeholder collaboration, Agile participation, cloud integration, mentoring, and recommending reliable engineering solutions. The role requires expertise in SQL Server, data warehousing, dimensional modeling, healthcare data compliance, and pharmacy industry standards.

Leads Revance’s enterprise business intelligence function, including the Power BI platform, BI development team, semantic layer, reporting standards, and self-service natural-language analytics. Partners with stakeholders and Data Engineering to deliver trusted, decision-ready insights. Oversees BI strategy, governance, data integrity, platform operations, project prioritization, and distributed team leadership while driving dashboard quality, adoption, and modernization.

Lead the strategy, roadmap, governance, standards, quality, and adoption of the enterprise payer data domain. Partner with executives, data stewards, custodians, product, technology, analytics, compliance, and operations teams to prioritize data products and initiatives. Own domain-level decisions, definitions, metadata, policies, KPIs, regulatory risk, and stakeholder alignment while supporting provider and healthcare data strategies across the organization.

Leads healthcare data architecture, modeling, normalization, transformation, and integration across FHIR, OMOP, STDM, HL7, and related standards. Oversees data pipelines, terminology mapping, deduplication, quality initiatives, interoperability strategies, and technical documentation. Collaborates across technical and non-technical teams to resolve complex data issues and explore AI and machine learning applications. Requires deep expertise in clinical informatics, healthcare data standards, SQL, Python, R, dbt, ETL, cloud platforms, and version control.

Supports business-impacting projects through data analysis, reporting, systems performance analysis, clinical insights, and innovation initiatives. Uses Excel, VBA, Power BI, and SQL while collaborating across the company to support SaaS products and build technical and interpersonal skills.

Leads Point C’s enterprise analytics strategy, data platforms, governance, reporting, and insights delivery. Builds trusted analytics for brokers, employers, sales, operations, finance, and clinical teams; oversees data integration, quality, standardization, and acquisition-related analytics. Develops a scalable agile analytics organization and aligns roadmaps, metrics, and delivery standards with business growth and executive decision-making.

Own data partner specification negotiations, data mapping, Ascend platform configuration, and internal QA across multiple implementations. Review file specifications, normalize schemas, validate test files, document data dictionaries, and route non-standard requests to Product or Customer Engineering. Coordinate with delivery and engagement teams on UAT, defects, readiness, and capacity constraints. Develop repeatable QA frameworks, implementation playbooks, procedures, and training materials while ensuring configurations meet quality standards before go-live.

Leads Data Operations, including reporting, dashboards, data warehouse and dbt model oversight, data quality, governance, service levels, incident response, and stakeholder prioritization. Manages and develops data professionals while partnering with Data Engineering, Security, Privacy, Compliance, and Enterprise Architecture. Ensures reliable, secure, well-documented data services and protects PHI through appropriate access, privacy, lineage, retention, and monitoring controls.

Leads a team delivering Customer Success reporting, dashboards, KPI frameworks, and operational analytics. Oversees reporting accuracy, data integrity, recurring metrics, workflow improvements, and automation. Partners with Customer Success and services leadership to translate business needs into analytical requirements, prioritize initiatives, standardize reporting methodologies, and communicate performance insights. Coaches analysts, manages workload and development, and supports data-driven operational decision-making and scaling.