Boston Scientific Lead Data Product Owner WATCHMAN 

United States, Minnesota, Maple Grove 

751057268

About the role:

Your responsibilities will include:

• Maintaining and delivering a comprehensive data product roadmap that outlines the vision, goals, and strategic direction for data management and analytics products. Continuously update the roadmap based on evolving business needs, technological advancements, and market trends.
• Collaborating with stakeholders to identify and understand business needs, translate them into use cases, and prioritize a plan based on strategic goals and team objectives.
• Leading the data modeling process by working closely with 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.
• Applying Agile best practices to direct and guide cross-functional teams, including data engineers, analysts, and data scientists, to execute project deliverables and achieve business objectives. Provide clear direction, prioritize tasks, and ensure efficient collaboration. Ensure releases are delivered on time, within scope, and meet quality standards.
• Effectively communicating project status, data insights, and technical concepts to business stakeholders, executives, and end-users.
• Recommending improvements to the data operating model, including governance, workflow, roles, and responsibilities necessary for effective and efficient delivery.
• Ensuring the platform architecture promotes data quality, security, scalability, and accessibility while supporting data-driven decision-making across the organization.
• Promoting the adoption of best practices in platform product management, focusing on an agile approach to Service Delivery Life Cycle (SDLC) methodologies, user-centered design, and continuous improvement.

Required Qualifications:

• Bachelor’s degree in computer science, software engineering, mathematics, statistics, or a related technical field, or 5+ years of equivalent professional experience.
• Hands-on experience with implementing modern data stack (MDS) technologies and frameworks, including data extraction, transformation, and loading (ETL/ELT) processes. Familiarity with tools like Snowflake, Apache Airflow, DBT, or similar technologies is required.
• Proven expertise in designing and implementing data models that facilitate accurate and efficient data analysis. Familiarity with modeling tools like DBT is required.
• Strong knowledge of SQL and relational database management systems (RDBMS).
• Familiarity with Amazon Web Services (AWS) cloud platform and its data-related services, such as Amazon Redshift, AWS Glue, or Amazon S3. Ability to leverage cloud-based solutions for scalable data storage, processing, and analytics is advantageous.
• Understanding of Machine Learning Operations (ML Ops) principles and practices, including model deployment, monitoring, and lifecycle management. Experience with platforms such as Sagemaker, Databricks, or similar is beneficial.
• Excellent communication and interpersonal skills, with the ability to align stakeholders and develop strong relationships, coach stakeholders who are not data-savvy, and fully leverage their knowledge and support.
• Experience managing Agile processes, including running daily standups, sprint planning sessions, and proactively creating and managing stories in JIRA.
• Strong analytical mindset, with an understanding of the key impact on customers and stakeholders.
• Demonstrated ability to identify inefficiencies and implement innovative solutions to improve processes and outcomes.
• Ability to operate independently with an entrepreneurial spirit.
• Ability to foster a culture of innovation within the data management team and stay informed about industry trends, emerging technologies, and best practices in platform product management.