Top Hybrid Data & Analytics Jobs in Boston, MA

The role involves analyzing large datasets to ensure compliance, translate analyses into insights for stakeholders, and improve compliance processes through data solutions.

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

The Principal Data Engineer will lead technical consulting efforts, manage data engineering projects, ensure quality control, and mentor team members while focusing on clinical data software and analytics solutions.

The role involves operating and improving AI-driven data quality pipelines, managing offshore teams, and ensuring data accuracy and reliability. Responsibilities include monitoring pipeline performance, refining rules, and collaborating across teams to enhance data operations.

The Principal Sales Operations Analyst will leverage data and advanced analytics to drive sales performance, optimize operations, and deliver insights while mentoring junior analysts and collaborating across departments.

As a Distinguished Data Engineer, you will lead the technical strategy for data pipelines, driving innovation and best engineering practices while mentoring internal teams and influencing stakeholders across the enterprise.

Lead the development of scalable data platforms and analytics systems, overseeing teams in building data pipelines, advanced algorithms, and dashboards for data-driven decision making.

The Senior Revenue Operations Analyst will support go-to-market teams with insights and reporting, optimize processes, and analyze revenue trends to drive operational efficiency and revenue growth.

Design the architecture for a healthcare data ecosystem, ensuring integration of structured and unstructured data for AI use, while maintaining data quality and governance.

Lead and grow an analytics engineering team to deliver scalable data models and reporting for Product, Marketing, Finance, and other stakeholders. Drive BI platform vision, collaborate with Product and Data Governance, prioritize work, implement agile practices, and ensure high data quality and performant transformations.