Top Senior Data & Analytics Jobs in NYC, NY

Analyze complex data and develop managed data solutions, business intelligence tools, dashboards, metrics, and self-service capabilities. Partner with business and technology teams to deliver strategic insights, manage data quality, metadata, lineage, security, and access governance. The role requires scripting, querying, visualization, Snowflake development, and familiarity with cloud services and data governance.

Support enterprise data governance by producing executive-ready materials, maintaining governance documentation, tracking controls-focused metrics and deliverables, coordinating stakeholders, and improving governance processes and communications across data, technology, risk, and control partners.

Build scalable customer experience data systems, pipelines, dashboards, metrics, and reporting frameworks. Analyze customer interactions and operational data to identify performance drivers, root causes, and improvement opportunities. Develop AI and LLM-powered quality assurance and feedback workflows, maintain data governance, and ensure analytics platform reliability. Partner with Customer Success, Support, Product, Engineering, and Data teams to deliver actionable insights and executive reporting. Manage NPS outreach and communicate recommendations to leadership.

Owns the design, development, operation, and governance of data pipelines and integration patterns supporting Medical Affairs AI products. Builds APIs and ETL/ELT solutions connecting enterprise systems to analytics platforms, RAG pipelines, vector databases, and GraphRAG applications. Ensures data quality, privacy, lineage, compliance, and protection of sensitive information. Partners with architecture, engineering, product, and business stakeholders to deliver reusable, production-grade data integrations.

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.

Design and scale lakehouse architecture, including Bronze, Silver, and Gold data layers. Build reliable streaming and batch pipelines with Kafka, Spark, and Airflow; manage Iceberg, Delta, and Hudi table formats; optimize Trino, Starburst, and Databricks queries; and improve platform reliability, data quality, and performance. Collaborate with data scientists, analysts, and product teams to deliver scalable data platform solutions.

Designs and maintains dashboards, reports, and visualizations; validates data quality and reporting logic; translates complex analysis into actionable recommendations; partners with data teams and stakeholders; improves reporting scalability, self-service analytics, and responsible AI usage. Presents findings to technical and non-technical audiences while supporting strategic and operational decision-making.

Own January’s trusted analytics layer by designing a dbt-driven semantic layer in Snowflake, standardizing metrics and data contracts, improving client reporting, expanding data capture, and managing analytics costs. The role enables trustworthy self-service across dashboards, chatbots, and future AI agents while partnering with Data Engineering, Analytics, Borrower Support, and Client Acquisition.

Provides analytics-driven strategic advice for mergers, acquisitions, and other transactions. Responsibilities include analyzing contract data, developing algorithms and predictive models, integrating data sources, building pipelines, creating dashboards, validating data integrity and security, and identifying risks and compliance indicators. The role also involves client collaboration, mentoring junior staff, and delivering data-driven insights using Python and machine learning.

Support firmwide rollout and execution of Critical Investment Data governance policy. Partner with COOs and data owners to implement standards, run governance forums, deploy tools, collect metrics, deliver training, and drive cross-business collaboration to ensure dataset compliance and measurable business impact.