Top Data & Analytics Jobs in NYC, NY

Produces automated and custom client-facing healthcare reports, translating ambiguous business questions into robust analyses and presentations. Builds scalable reporting automation with data engineering partners, improves report efficiency and accuracy, identifies reporting gaps, develops domain expertise, and investigates complex business questions for strategic decision-making. Advocates for strong data visualization, documentation, metric consistency, and stakeholder communication practices.

The Senior Data Engineer will design and maintain data pipelines, build reusable data sets, validate data integrity, and ensure user privacy and security. This role requires strong expertise in SQL and Python, and familiarity with AWS and various data technologies.

The Data Engineer II will build and optimize data pipelines, develop reusable data sets, and ensure data integrity and security.

Lead a small analytics team to design experiments, run causal analyses, and build measurement frameworks. Partner with Product, Engineering, and leadership to translate complex analyses into actionable recommendations, manage A/B testing and causal methods, mentor analysts, enforce analytical standards, and own measurement strategy across growth and product.

Build and govern KPIs and dashboards, partner with stakeholders on measurement, develop scalable data pipelines, run deep-dive analyses, close reporting gaps, and promote best practices in visualization and metric consistency.

Partner with client-facing teams to deliver and automate high-quality, scalable client reports and custom analyses using Snowflake/SQL and modern data tooling. Improve report accuracy, documentation, visualizations, and drive insights for strategic decisions.

Lead end-to-end analytics: own KPIs and dashboards, define measurement with stakeholders, build scalable pipelines with Data Engineering, run deep-dive analyses, close reporting gaps, and advocate best practices in visualization, documentation, and metric consistency to inform business strategy.

Own implementation, maintenance, and optimization of client eligibility and claims data feeds. Analyze feed performance, troubleshoot discrepancies, produce error reports, test integrations with external partners, and improve internal tools, documentation, and processes to increase automation and reliability.