Data Product Owner

A Data Product Owner (DPO) serves as the critical bridge between data and AI teams and business stakeholders, ensuring that data products deliver measurable value aligned with business objectives. The DPO oversees the entire data product lifecycle — from defining the product vision and prioritizing use cases to deployment and continuous optimization.

Acting as a translator between business needs and technical implementation, the DPO ensures that data products are strategically aligned, technically feasible, and effectively adopted by end users. This role is central to driving data-driven decision-making and maximizing return on data investments.

Key Responsibilities:

• Define the purpose, goals, and success metrics of data products, aligning them with business objectives.
• Understand user needs and translate them into clear and actionable product requirements.
• Manage the product backlog by prioritizing features and tasks based on business impact and technical feasibility.
• Work closely with stakeholders (e.g. Business SPOCs, CRM Teams, CDAO, CDMO) to gather reporting requirements and expectations.
• Collaborate with data scientists, data engineers, and developers to deliver scalable, high-quality data solutions.
• Track and report on Key Performance Indicators (KPIs) to evaluate the success of the product and identify areas for improvement.
• Ensure all data products meet data governance, privacy, and compliance standards.
• Facilitate workshops with business and technical teams to align on requirements, progress, and delivery plans.
• Coordinate with global teams (e.g., L’Oréal IT, LTIM SPACE team) to finalize and transform Excel-based reports into scalable BI reports.
• Perform tactical analysis to understand reporting requirements, map them to business zones, and support technical implementation.
• Translate a high volume of business reports into structured development tasks and product deliverables.

Required Skills & Qualifications:

• Strong experience in the CPG domain and exposure to data initiatives across other industries.
• Proven ability to work closely with business, IT, and project teams to gather and interpret requirements.
• Strong knowledge of data analysis, including trends interpretation and actionable insight generation.
• Proficiency in SQL for querying and analyzing structured data.
• Familiarity with Power BI or any other data visualization tool (preferred, not mandatory).
• Solid understanding of data visualization principles.
• Excellent interpersonal and communication skills to work across technical and non-technical teams.
• Tactical thinking with the ability to manage large sets of reporting tasks and KPIs.
• Understanding of AI/ML concepts is a strong plus.

This position is open to all who are fulfilling aforesaid requirements.