Top Data & Analytics Jobs in Boston, MA

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

Partner with Operations, Demand Planning, Logistics, Supply Chain, and Finance to deliver analytics for S&OP, demand velocity, inventory and logistics optimization. Analyze shipping and inventory issues, recommend process improvements, maintain trusted metrics and semantic layer, and support cross-functional initiatives with scalable data solutions.

The Analytics Engineer will build and optimize data transformation models, assist with BI tools, support stakeholders, document processes, and implement AI tools, contributing to a data platform under mentorship.

Design, build, and maintain enterprise ETL/ELT pipelines and data management workflows for market, reference, and financial data in the Markit EDM platform. Implement ingestion, validation, reconciliation, enrichment, monitoring, and distribution processes; support reporting and downstream integrations. Troubleshoot production data issues, collaborate with stakeholders in agile squads, and mentor junior engineers to promote best practices.

The Senior Pricing and Packaging Analyst will analyze data to inform pricing strategies, develop recommendations, and work collaboratively across teams to implement these strategies.

Lead end-to-end analytics for Veterinary Diet, Science Diet, and Health & Wellness businesses. Build self-service dashboards, define KPIs, run deep-dive analyses, partner with technical and category teams, and deliver insights that improve customer experience and financial P&L.

Lead the transformation of People Analytics into a strategic, predictive, AI-enabled function. Define vision, operating model, and roadmap; build and lead a high-performing team; drive adoption of analytics and AI; partner with senior leaders on talent and organizational decisions; modernize analytics products, data foundations, and governance.

Lead redesign of the Customer Success unified data model and AI data strategy. Build and optimize pipelines, integrations (contact center), testing/monitoring, and a documented semantic layer. Manage and mentor a small team, partner cross-functionally on KPIs, governance, and data quality, and ensure CS data is reliable for dashboards, reporting, and AI use cases.

Lead operational design and engineering for the data platform: own Snowflake and dbt administration, automate platform operations and CI/CD, monitor platform health and observability, enforce governance and access, optimize performance and costs, and develop AI/agent integrations to enable governed data access for business users.