Top Data & Analytics Jobs

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.

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.

Own end-to-end client reporting and analysis, including scoping, delivery, automated report development, and deep-dive investigations. Partner with client-facing teams to answer complex healthcare questions, improve report efficiency and accuracy, develop scalable reporting automation with data engineering, and establish best practices for visualization, documentation, metrics, and stakeholder communication.

Leads Garner’s Data Platform Engineering team, overseeing scalable healthcare data infrastructure, pipelines, abstractions, and distributed processing systems. Provides hands-on architectural guidance, establishes engineering standards, translates business requirements into technical roadmaps, and promotes AI-native development practices. The role includes hiring, mentoring, stakeholder management, design reviews, root cause analysis, and operational excellence while supporting rapid enterprise data growth.

Build, optimize, and maintain scalable data pipelines and reusable datasets for business intelligence, marketing, and data science. Develop federated data validation frameworks, optimize queries and data models, and protect user privacy and security. The role uses Python, SQL, AWS, Airflow, PostgreSQL, Iceberg, Snowflake, Spark, and other modern data-stack technologies. It is based in New York City with in-office work three days per week.

Build, optimize, and maintain scalable data pipelines and reusable datasets for business intelligence, marketing, and data science. Design a federated data validation framework, optimize queries, support data modeling and governance, and protect user privacy and security. The role uses Python, SQL, AWS, Airflow, Snowflake, PostgreSQL, and other modern data-stack technologies, with a hybrid schedule requiring three days weekly in the New York City office.

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.

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.