Top Healthtech Data & Analytics Jobs

Leads marketing media measurement strategy across Social, TV, Influencer, and Content Marketing. Owns Marketing Mix Modeling, incrementality testing, causal inference, attribution, experimentation, and media effectiveness analysis. Uses SQL and statistical programming to evaluate customer and media data, develop investment recommendations, and communicate findings to executives. Partners cross-functionally with Marketing, Finance, Data Science, Engineering, Product, and agencies while leading analytics talent and remaining hands-on.

Leads the design, development, and operation of scalable data platforms and ETL/ELT pipelines using Python, PySpark, Databricks, Spark, Delta Lake, and cloud services. Responsibilities include data modeling, performance optimization, governance, lineage, quality validation, security, compliance, CI/CD, monitoring, AI/ML enablement, and data product delivery. Partners with stakeholders and mentors engineers while supporting reliable enterprise healthcare data solutions.

Supports an internally developed financial application processing healthcare data for accounting and journal entries. Analyzes clinical practice management and financial data, develops complex SQL and stored procedures, investigates data issues, and supports integrations, validation, reconciliation, reporting, and production processes. Translates business needs into technical requirements, mappings, testing plans, and documentation while improving data quality, controls, automation, and governance. Partners across Finance, Accounting, Revenue Cycle, Analytics, Engineering, and Technology, providing technical leadership without direct people management.

Leads a client-facing healthcare analytics team that designs and maintains prior authorization decision automation programs. Consults PaaS clients, develops strategic roadmaps, translates requirements into technical blueprints, analyzes authorization and claims data, and builds KPI reports using visualization tools. Manages direct reports, improves analytics processes and AI tooling, partners with product and engineering teams, and ensures automation outcomes and client KPIs are achieved.

Design, build, and operate batch, streaming, and hybrid data pipelines in a regulated healthcare environment. Develop dbt models in BigQuery, ingest structured and unstructured clinical data, and implement data quality, lineage, governance, and compliance controls. Support ML workflows, CI/CD, monitoring, incident response, and platform architecture. Collaborate with data scientists, clinical, quality, security, and product teams while mentoring engineers and establishing standards.

Own wholesale performance reporting and analysis across retail partners, products, and regions. Build datasets, data models, dashboards, and automated reporting while validating data quality. Analyze sell-through, inventory, pricing, promotions, and commercial trends to identify growth opportunities. Partner with stakeholders across Wholesale, Digital Commerce, and Marketing to frame analytical questions, communicate findings, and provide actionable recommendations.

Build, optimize, and maintain scalable data pipelines and reusable datasets for business intelligence, marketing, and data science. Develop a federated data validation framework, optimize queries and data models, and protect sensitive healthcare data through privacy and security best practices. The role uses Python, SQL, AWS, Airflow, PostgreSQL, Snowflake, and modern data-stack technologies. This position is based in New York City and requires working onsite three days per week.

Leads site data, integration, and systems capabilities within a regulated manufacturing environment. Owns data strategy, governance, standards, system integrations, historians, data platforms, application lifecycle management, and AI enablement. Ensures compliant, reliable, contextualized manufacturing data while maintaining validation and inspection readiness. Manages the data enablement roadmap, resolves data quality and connectivity issues, supports analytics and AI deployments, and leads technical teams, contractors, and cross-functional stakeholders.

Develop and optimize advanced SQL transformations, stored procedures, ETL workflows, and data-quality processes for large Medicaid claims and health-related social needs datasets. Build reproducible, documented data pipelines; calculate healthcare quality, equity, and disparity metrics; conduct code reviews; and collaborate with stakeholders to turn complex data into visualizations and policy insights.

Validate and review CO APCD-derived data products using SQL and visualization tools, perform output comparisons and project-level analyses, follow quality control standards, document findings, and communicate results to technical and non-technical stakeholders while supporting continuous improvement of data QA processes.

Build and maintain Databricks data pipelines using SparkSQL and PySpark; ingest, transform, model, and validate healthcare data from payer, provider, platform, and API sources. Support automated file exchanges, dashboards, downstream workflows, testing, governance, access controls, and audit logging. Participate in design and code reviews, use AI coding tools responsibly, and progressively own data engineering work while handling protected health information.