Product Owner Data Analytics - Lead

Job Description

I. Key Responsibilities

 A. Strategy & Vision

• Define and own the product vision and strategy for the Data and Analytics portfolio, including data pipelines, data warehouses/lakes, reporting tools, and predictive models.
• Work closely with executive stakeholders, department heads (e.g., Marketing, Finance, Operations), and end-users to gather, analyze, and prioritize business requirements for data and reporting needs.
• Maintain and prioritize the Data Product Backlog (features, user stories, acceptance criteria, and technical debt) to maximize business value delivered by the team.

 B. Execution & Delivery

• Translate high-level business requirements into detailed user stories and clear acceptance criteria for the Data Engineering and Analytics teams.
• Lead Agile ceremonies for the data team, including sprint planning, backlog grooming, and sprint reviews.
• Accept or reject user stories based on the Definition of Done, ensuring the data product meets quality, performance, and security standards (e.g., data accuracy, latency).
• Collaborate with Data Architects and Engineers to make key decisions regarding data models, governance, and technology selection for new initiatives.

 C. Stakeholder Management & Communication

• Serve as the primary liaison between the business stakeholders and the technical development team.
• Communicate the status, dependencies, and value of the data roadmap and delivered features clearly and regularly to stakeholders at all levels.
• Demonstrate delivered functionality (e.g., new dashboards, data sets, or API endpoints) to business users, gathering feedback for future iterations.
• Manage dependencies across multiple data teams and other product teams that consume the central data assets.

II. Required Qualifications & Skills

 A. Experience

• 3+ years of experience as a Product Owner, Business Analyst, or similar role focused specifically on data, business intelligence (BI), or reporting platforms.
• Proven experience working within an Agile (Scrum/Kanban) framework.
• Demonstrated success in defining and launching data products or analytical features.

 B. Technical & Data Fluency

• Strong proficiency in SQL and experience working directly with relational (e.g., PostgreSQL, SQL Server) and/or NoSQL databases.
• Working knowledge of data warehousing concepts (e.g., dimensional modeling, Kimball/Inmon approaches), ETL/ELT processes, and data quality principles.
• Familiarity with modern BI tools and visualization platforms (e.g., Tableau, Power BI, Looker).
• Understanding of the difference between transactional (OLTP) and analytical (OLAP) data systems.

 C. Leadership & Soft Skills

• Exceptional analytical and problem-solving skills with a clear ability to break down complex data problems into manageable components.
• Excellent written and verbal communication skills, with the ability to convey technical concepts to non-technical business leaders and vice-versa.
• High level of initiative, self-motivation, and the ability to work independently in a fast-paced environment.

Mandatory Competencies