Top Healthtech Data & Analytics Jobs

Own commercial analytics for direct-to-consumer and marketplace channels, analyzing pricing, promotions, conversion funnels, merchandising, product mix, customer behavior, and channel economics. Build scalable reporting tools, support forecasting and planning, and translate transactional and behavioral data into recommendations for digital commerce leadership. Partner with Marketing Analytics and Analytics Engineering to connect acquisition trends with commercial outcomes and ensure trusted data.

Owns Pfizer GH&B’s AI-ready Snowflake data warehouse, data architecture, ontologies, governance, quality, lineage, access controls, and production reliability. The role supports AI/ML models, dashboards, and business-critical data applications; establishes testing, release, monitoring, and incident processes; directs contingent technical resources; and aligns business-specific data decisions with enterprise standards. Requires strong SQL, Python, Collibra, data warehousing, unstructured-data architecture, ontology, governance, and stakeholder-influence experience.

Maintain global ERP master data, item and branch records, BOMs, planning parameters, MRP data, and supply chain documentation. Analyze data quality issues, support reporting and dashboards, ensure compliance with SOX and GMP requirements, and collaborate with Manufacturing, Quality, Regulatory, Finance, and planning teams. The role also contributes to process improvements, ERP enhancements, and transformation initiatives.

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.

Designs and maintains scalable data pipelines and infrastructure, establishes data governance and quality standards, and drives technical decisions across Headway’s data platform. Partners with Product, Engineering, Analytics, Data Science, Infrastructure, Finance, and Insurance Systems to improve architecture, performance, reliability, security, and AI-readiness. Ensures data is complete, traceable, trustworthy, and suitable for powering internal tools and AI-driven insights.

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.

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.

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.

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.

Create client-facing analyses and reusable data products for Product, Analytics, Client Success, and Sales teams. Analyze large healthcare datasets to identify behavioral patterns among medical professionals, automate code, and communicate insights to technical and non-technical stakeholders. The role combines SQL, Python-based exploratory data analysis, data visualization, stakeholder collaboration, and opportunities to grow into presentation-focused or advanced technical work.