Data Product Leader - Snowflake BI Platform

Boston Scientific

Maple Grove (MN)

Hybrid

USD 126,000 - 239,000

Full time

14 days+

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Job summary

Boston Scientific seeks a Senior Manager of Data Products to lead the Snowflake-based commercial data platform, guiding data product managers and analysts. You will drive BI focus, enable scalable analytics, and partner with IT, Sales Ops, and Marketing to meet evolving commercial needs.

The role centers on data quality, governance, and AI-ready analytics, with hybrid work expectations. This leadership position requires 8+ years in analytics/data product leadership within healthcare, strong

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.

Responsibilities

Develop and drive the Cardiology BI 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.