Senior Manager, Data Products

At Boston Scientific, we advance science for life by ensuring that data fuels smarter decisions, stronger customer engagement, and improved patient outcomes. The Senior Manager, Data Products role owns the vision and roadmap for our Snowflake-based commercial data platform as we lean into a broader Business Intelligence focus and leads a team of Data Product Managers and Analysts responsible for delivering scalable, high-quality data products, data exploration capabilities and self-service analytics.

This role is central to enabling data‑driven commercial excellence. You will collaborate closely with IT, Sales Operations, Business Leadership and Cardiology Marketing to ensure our data products support evolving business needs, enable deeper analytical insights, and provide a strong foundation for advanced analytics and AI/ML use cases.

At Boston Scientific, we value collaboration and synergy. This role follows a hybrid work model requiring employees to be in our local office at least three days per week. Boston Scientific will not offer sponsorship or take over sponsorship of an employment visa for this position at this time. Relocation assistance is not available for this position at this time.

• Develop and drive the Cardiology Business Intelligence data strategy, aligning Snowflake platform development with business priorities and evolving analytics needs.
• Identify and champion innovative technologies, architectural enhancements, and automation opportunities to increase data velocity, flexibility, and scalability.
• Influence IT and enterprise stakeholders to invest in data capabilities that advance strategy, forecasting, segmentation, field effectiveness, and more advanced analytical approaches.
• Lead multi‑year planning for data platform evolution, ensuring technology investments support long‑term analytics maturity, including readiness for advanced analytics and AI.
• Design & oversee the change management strategy for key data initiatives.

• Oversee the lifecycle of data products, including requirements definition, design, prioritization, and delivery in partnership with engineering teams.
• Define and manage the data product portfolio, ensuring alignment with business needs and technical capabilities.
• Ensure data products meet requirements for downstream analytics, dashboards, reporting, and advanced analytics use cases, including those that support modeling and AI/ML initiatives.
• Establish processes for data quality measurement, metadata standards, lineage transparency, and ongoing product enhancement.
• Lead, mentor, and develop a team of Data Product Managers, fostering a culture of curiosity, innovation, accountability, and continuous improvement.
• Establish clear roles for each Data Product Manager and define Analyst roles on the team.
• Build career pathways, ensure clarity in role expectations, and empower team members to become strategic partners to the business.
• Create an inclusive environment that values diverse perspectives and encourages experimentation, scenario testing, and creative solutions to business challenges.

• Build trusted partnerships across Commercial Analytics, IT Data Engineering, Sales Operations, Marketing, and Global Business Services to ensure alignment and value delivery.
• Facilitate cross‑functional forums to harmonize data definitions, improve master data practices, and prioritize enhancements based on business impact.
• Partner with strategy and analytics teams to support and enhance business problem solving projects, ensuring data products effectively support advanced analytics, forecasting, and modeling efforts.
• Communicate roadmap progress, dependencies, and risks effectively to executive stakeholders, ensuring transparency and alignment.

• Ensure the Snowflake platform is optimized for performance, availability, cost, and data security in partnership with IT.
• Establish KPIs and SLAs for data reliability, latency, adoption, and data product performance.
• Drive process standardization, automation, and continuous improvement across the commercial data ecosystem.