Top Hybrid Senior Level Data & Analytics Jobs in Boston, MA

Develop scalable, reusable data and reporting solutions, production pipelines, dashboards, and proof-of-concepts. Apply data engineering, quality testing, metadata, lineage, compliance, and security practices while optimizing infrastructure performance, reliability, and cost. Evaluate emerging tools and GenAI applications, collaborate with technical and business stakeholders, prioritize customer value, and mentor junior team members.

Supports Fund Management through regulatory communications, cost allocation, operational reporting, and analytics. Develops and maintains Access, Excel, SQL, and enterprise reporting solutions; integrates data across systems; improves data quality and workflows; and supports testing, validation, deployment, automation, and AI-enabled process enhancements. The role also serves as a technical subject matter expert and coordinates regulatory reporting while driving efficiency and cost savings.

Design and build data validation, integration, and transformation solutions to support ERP implementations and risk/regulatory clients. Develop data pipelines and infrastructure, manage data validation processes, ensure data lineage and quality, manipulate large datasets using Excel, Alteryx, SQL, Python, Databricks, or Snowflake, and collaborate with clients to deliver scalable, governed data solutions.

Manage the data architecture and strategic planning for the Sales team, optimizing processes through data and AI for targeting accounts and pricing strategies.

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 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.

Design, build, and own the full data platform (ingestion, modeling, CI/CD, orchestration, observability, and BI). Implement streaming and batch pipelines for IoT data, enable governed self-service, enforce data governance/privacy/security, evolve AI access patterns, and provide technical leadership and mentorship to data engineers and data scientists to deliver production-ready analytics and ML capabilities.