Snowflake Data Engineer and Product Owner

This is a remote position.

Our client is embarking on an implementation journey with Snowflake and seeks a skilled Data Engineer and Product Owner to manage the Snowflake data analytics solution.

Overview: The Snowflake Product Owner will be responsible for managing tasks and deliverables within the project schedule and will act as the primary contact between the data team and project stakeholders. This individual must possess a strong working knowledge of data management principles and have experience with data engineering and visualization projects.

Responsibilities:

• Product Vision and Strategy: Take ownership of the Snowflake data solution and business intelligence product, defining the product vision, strategy, and roadmap.
  
• Technical Collaboration: Attend Data and Analytics technical meetings.
  
• Stakeholder Engagement: Collaborate with business stakeholders to gather and understand their data and reporting needs. Translate these requirements into actionable tasks for the development team.
  
• Team Coordination: Work closely with data engineers, data analysts, and business intelligence developers to ensure the successful execution of product features and enhancements.
  
• Architecture and Development Consulting: Consult on architecture design, data enablement, development, and other related activities.
  
• Agile Methodology Implementation: Partner with the client to establish an Agile Scrum methodology and process that supports both Project Transformation and broader Enterprise-wide reporting and analytics requirements.
  
• Scrum Leadership: Act as the scrum leader in the development of automated data pipelines and analytics for assigned portfolios.
  
• Backlog Management: Manage the data backlog and address delivery blockers.
  
• Progress Reporting: Report project progress to the leadership team.
  
• Sprint Leadership: Lead sprint ceremonies, remove roadblocks, and ensure stories are complete and accurate.
  
• Team Dynamics: Promote healthy team dynamics and execution.
  
• Quality Assurance: Ensure testing scenarios are designed and executed to ensure high-quality data.
  
  

Requirements