Top Senior Data & Analytics Jobs in Boston, MA

The Senior Data Engineer will architect AI infrastructure, design high-performance data systems, manage AI pipelines, and collaborate with cross-functional teams. Responsibilities include implementing data architecture best practices and providing documentation and leadership in data orchestration.

The Principal SAP PaPM Configuration Engineer analyzes and configures use cases, supports production users, and mentors team members to enhance SAP PaPM systems within the finance environment.

The Manager of Media Analytics & Optimization will lead media performance measurement, drive insights for decision-making, and foster collaboration with senior stakeholders, while utilizing skills in analytics and AI.

The Resource Planning and Management Analyst documents business requirements, supports process mapping, collaborates with stakeholders, and analyzes data to provide insights and enhance solutions.

The Business Analytics Manager will partner with Lifecycle Marketing to enhance member communications, drive engagement, and inform strategic decisions using data analysis and insights.

Lead Data Product Management for G&A functions, shaping strategy, coordinating execution, and establishing practices within Finance, HR, and IT sectors. Engage stakeholders, ensure data quality and governance, and manage team growth while directly overseeing product delivery.

As a Senior Data Engineer, you'll design scalable data models, build automated ETL pipelines, and mentor junior engineers while collaborating across teams.

Responsible for architecting the sales data ecosystem, ensuring data integrity, governance, and providing real-time insights for forecasting and revenue decision-making.

As a Salesforce TPM Manager, you will lead Trade Promotion Management implementations, translate requirements into solutions, mentor teams, and foster client relationships while ensuring adherence to project quality and timelines.

The Senior Analytics Engineer will develop data infrastructure, optimize data systems, ensure data quality, and collaborate on scalable data models and pipelines, focusing on analytics support.