Data Product Manager, Cardiology Sales Ops

Additional Location(s): US-MN-Maple Grove

Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance

At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions.                

About the role

Boston Scientific’s Cardiology Sales Operations franchise is growing and is seeking an experienced Data Product Manager to support our data maturity efforts.

We are looking for an experienced data product manager who can balance the strategy, governance, and implementation of key data that will be leveraged by multiple functions within Cardiology Sales Operations. Partnering closely within the Data & Analytics team in Cardiology Sales Ops Strategy, this role is responsible to bridge the gap between business strategy, data science, engineering and user experience to deliver data-driven solutions. This role balances highly technical acumen with deep business context, understanding not only the intricacies of how data flows and is consumed, but also what data is most valuable to drive business results. If you are a driven individual with a strong technical background, excellent problem-solving skills, and a passion for leveraging data to drive business decisions, we would love to hear from you. Join our team and contribute to the success of our data-driven initiatives.

 

Your responsibilities will include:

• Collaborate with stakeholders to identify and understand business needs for data, translate them into use cases, and prioritize a plan based on strategic goals and value.
• Bring business knowledge and context to data, while understanding the technical aspects of all source systems of data. Troubleshoot data flow discrepancies/accuracy and help problem solve data opportunities.
• One of the primary contacts that interfaces with IT (Product Manager, Tech Lead, Engineers) to import new data, troubleshoot/test data and establish/maintain data governance.
• Work closely with other data product managers, data engineers, architects, and analysts to define and refine data models that meet business requirements. Ensure data models align with organizational standards and support efficient data analysis and reporting.
• Effectively communicate project status, data insights, and technical concepts to business stakeholders, executives, and end-users.
• Recommend improvements to the data operating model, including governance, workflow, roles, and responsibilities necessary for effective and efficient delivery. Establish and maintain data policies, standards and guidelines to govern data usage and security/access provisions, including maintaining data dictionaries, lineage and metadata in collaboration with IT.
• Ensure the platform technical architecture promotes data quality, security, scalability, and accessibility while supporting data-driven decision-making across the organization.

Required Qualifications

• Bachelors Degree in Engineering, Mathematics, Statistics, Data Science or related technical field or equivalent experience.
• 5+ years demonstrated experience with digital technology development, product management, product design, or product engineering for a platform product.
• Modern Data Stack (MDS) Experience: Hands-on experience with implementing modern data stack technologies and frameworks, including data extraction, transformation, and loading (ETL) processes. Familiarity with tools like Snowflake, Apache Airflow, DBT, or similar technologies is a plus.
• Strong Data Modeling Experience: Proven expertise in designing and implementing data models that facilitate accurate and efficient data analysis. Familiarity with modeling tools like Tableau Prep & Alteryx is required, experience in DBT and python is a plus.
• Proficiency in SQL: Strong knowledge of SQL and relational database management systems (RDBMS). Ability to write complex queries, optimize performance, and extract insights from large datasets.
• Excellent communication and