Jobs · OTHR · Minnesota

Senior Manager, Data Products

Boston Scientific · Maple Grove, MN · 2 days ago
OTHR$126k/yrFull-time

About the role

The Senior Manager, Data Products role at Boston Scientific owns the vision and roadmap for our Snowflake-based commercial data platform. This role is central to enabling data-driven commercial excellence.

Responsibilities

  • 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.
  • Build clear roles for each Data Product Manager and define Analyst roles on the team.
  • Create career pathways, ensure clarity in role expectations, and empower team members to become strategic partners to the business.
  • 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.
  • Determine process standardization, automation, and continuous improvement across the commercial data ecosystem.

Qualifications

  • Bachelor’s degree in Data Management, Computer Science, Business Analytics, or related field; Master’s preferred and/or equivalent experience.
  • 8+ years of experience in commercial analytics, data product leadership, or data management within medical device, healthcare, or life sciences organizations.
  • Proven expertise managing Snowflake or similar cloud data warehouse platforms.
  • Strong understanding of sales operations data, CRM systems (Salesforce/Veeva), and syndicated market data sources (IQVIA, Symphony, DRG/Clarivate, commercial claims).
  • Experience managing and developing high-performing teams and leading complex cross-functional initiatives.

Preferred Qualifications

  • Proficiency with BI tools (Tableau, Power BI, Looker, Sigma) and modern ELT technologies (e.g., dbt).
  • Experience with Agile delivery methodologies and data product management frameworks.
  • Exposure to advanced analytics, data science, or AI/ML-enabled use cases within a business environment.
  • Demonstrated success influencing technology and investment decisions across IT and business leadership.

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