Top Senior Level Data & Analytics Jobs in Boston, MA

Own the design, governance, and evolution of the enterprise data lake and warehouse. Responsibilities include developing conceptual, logical, and physical data models; defining source-to-target mappings; reconciling legacy CRM and operational data; establishing data quality frameworks; administering schemas, views, access controls, and performance; and partnering with engineering and business stakeholders to support scalable, self-service analytics.

Build and scale continuous monitoring and anomaly detection for Personal Lines Auto pricing programs. Analyze large datasets to detect issues, improve data quality, automate reporting, create dashboards and frameworks, and communicate findings to technical and business stakeholders. Partner cross-functionally to investigate root causes and support program-level monitoring for launched pricing programs.

Design, build, and operate high-throughput data pipelines supporting billing and cost attribution. Drive Spark optimization, latency reduction, sharding, cross-datacenter reliability, and new billing capabilities. Investigate billing accuracy issues with Finance and Product teams, participate in on-call rotation, and improve engineering standards and operational excellence.

Lead commercial analytics to diagnose sell-through, pricing, promotions, assortment, and retailer execution. Build causal and incrementality measurement, design test-and-learn, support elasticity and margin analyses, and deliver executive-ready insights and frameworks to optimize revenue, margin, and promotional efficiency across channels and retailers.

Support Business Banking with analytics, reporting, dashboards, and automation to drive deposit acquisition, onboarding, funded balance growth, and retention. Produce forecasting and pipeline reporting, provide deposit strategy and profitability insights, enable go-to-market and campaign analysis, and standardize onboarding and data processes to improve efficiency and data quality.

Lead the strategy and execution of real-world data capabilities, focusing on data lifecycle management, vendor relationships, and collaboration with various teams to deliver analysis-ready datasets.

Build and productize externally consumable data assets from concept to delivery. Define schema, governance, SLAs, documentation, and delivery (Snowflake share, SFTP, API). Partner cross-functionally to productionalize datasets, monitor quality, iterate on customer feedback, and create repeatable productization frameworks.

Lead design and implementation of data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Ensure data governance, security, cloud deployments, performance and cost optimization. Coach and manage team members, partner with stakeholders, and drive data-driven solutions for clients.

Design, build, and maintain high-throughput data processing services, focusing on streaming and batch data systems to enhance player experiences.

Lead enterprise healthcare data modeling: design and maintain conceptual/logical/physical models, integrate varied clinical sources, implement common data model transformations, monitor data quality, and collaborate with clinicians, data scientists, and engineers.