Top Senior Data & Analytics Jobs in NYC, NY

Advise business and company functions using performance metrics and population analysis to drive strategy, maximize profit and minimize loss within risk limits. Lead adoption of analytic tools/methods, ensure compliance, manage project updates, budgets and forecasts, support quarterly/annual planning, and collaborate with mid-to-senior managers. Hybrid role with up to two remote days; in-person presence required.

Lead data analysis projects to help merchant partners understand Upside's impact, manage analytics relationships, and improve product strategy.

Lead and grow a data engineering team, define data platform architecture and reliability (warehouse, ingestion, transformations, orchestration), set engineering standards, partner cross-functionally to support analytics and ML, and translate technical decisions for executive stakeholders.

Manage and grow an analytics engineering team while designing, building, and maintaining scalable ELT pipelines, dimensional data models, and reporting solutions. Partner with cross-functional teams to deliver high-quality, documented data products, uphold data quality, and drive adoption of self-service analytics.

Lead analytics engineering efforts to design and build dbt models, maintain a semantic/metrics layer, ensure Snowflake performance, establish modeling/testing/documentation standards, partner with Data Science/Product/Engineering, and deliver native warehouse data products to customers.

Own end-to-end data migrations for new customers: audit, clean, map, transform, import and validate legacy data using Rubie, SQL, JavaScript/Python and Excel. Build reusable mapping templates and documentation, work directly with customers and engineers, support post-go-live data issues, improve migration tooling, and track migration status in Planhat.

The Senior Revenue Operations Analyst will ensure data quality across systems, integrate third-party data into CRM, define quality metrics, and collaborate cross-functionally to improve data processes.

As a Data Analytics Engineer, you'll build and manage data models in Snowflake, structure datasets for optimal AI performance, and own data transformation while ensuring quality and accessibility for all teams.

Lead analytics and metrics for Customer Experience and Disputes: set and track KPIs, build scalable reporting and dashboards, modernize analytics infrastructure, translate business needs into models and executive storytelling, and manage a global team of data analysts.

Lead data strategy and analytics for Compliance, focusing on Financial Crimes/AML. Drive ETL, source validation, and analyses to quantify compliance risk, support regulatory engagements, and influence product and compliance roadmaps. Communicate insights through visualization and cross-functional collaboration while leading multiple high-impact workstreams.