The Data Products & Stewardship Manager is responsible for managing the lifecycle of division and function data products, including dashboards, reports, datasets and future AI-enabled data products - from ideation through delivery, adoption and continuous improvement. The role acts as a bridge between division and function stakeholders and data delivery teams, working closely with the business to proactively identify opportunities and use cases that can accelerate intelligence, activation, and value creation in achieving SEAA’s LEAP ambition. The role also serves as the primary point of contact for data-related queries, driving data stewardship practices across the region. This includes facilitating the clarification of data definitions and business logic, supporting data quality issue resolution, and helping establish trusted sources of data - while ensuring that ownership and accountability for data accuracy remain with the business domains and corporate functions that produce it.
Impact You Can Create In The Role:
Data Stewardship and Governance Facilitation:
- Act as the primary facilitator of data stewardship practices across SEAA, driving alignment on data definitions, business logic and data quality standards.
- Partner with divisions and corporate functions to define the scope of data under the governance framework, with a focus on Critical Data Elements.
- Ensure clear standards and policies are defined for Critical Data Elements, while coordinating with business domains to validate definitions and resolve data quality issues.
- Drive the adoption of data stewardship practices across business teams by embedding clear frameworks, tools and ways of working into day-to-day operations, ensuring governance is applied consistently without creating unnecessary complexity
Data Quality Management:
- Work with business stakeholders to identify and facilitate the production of Data Quality Rules and Data Quality Reporting.
- Identify processes that generate data quality issues and provide analysis and recommendations.
- Lead the identification, recording and escalation of data quality issues, partnering with the responsible business teams to drive remediation
Data Product Lifecycle Management in Divisions / Functions:
- Actively work with divisions and functions to identify high-value opportunities / use cases where data products, analytics or AI-enabled products can support growth, improve decision-making and accelerate activation towards LEAP ambition.
- Serve as the primary point of contact for divisions and corporate functions to gather, clarify, and prioritize data requirements and need.
- Oversee the lifecycle of all divisional / functional data products (including dashboards, reports, datasets, and future analytics / AI-enabled products), from ideation through delivery, adoption, and continuous improvement. Ensure data products provide relevant, timely, and actionable insights for business decision-makers
- Own the product backlog - define what data products to build, in what order, based on business value, feasibility and resource capacity. Work with the Data Platform & Engineering team, who own the technical design and implementation.
- Coordinate and manage the workflow for data and BI engineering teams, ensuring timely and accurate delivery of data solutions.
Business partnership and product adoption:
- Ensure business requirements are clear, granular and ready for engineering and analytics teams to deliver with minimal rework
- Drive adoption of data products, strategic KPIs and self-service analytics capabilities by guiding business users and promoting consistent use of a single source of truth.
Continuous Improvement:
- Identify opportunities to streamline data operations, improve data governance, and enhance reporting and analytics capabilities. Capture feedback and drive enhancements to improve adoption and business impact.
Your Success Measures
- Data Quality & Fit-for-Purpose: High levels of accuracy, completeness, consistency and usability are maintained across division data and relevant corporate data assets.
- Adoption & Usage: Increased usage of dashboards, datasets and data products by target business users.
- Requirement Readiness: Business requirements are clear, granular and ready for BI, engineering and analytics teams to deliver with minimal rework.
- Prioritization Discipline: The product backlog is actively managed, with clear rationale for what is prioritized, phased or declined - ensuring team capacity is focused on highest-value outcomes.
- Issue Resolution: Data-related issues are identified, escalated and resolved in a timely manner.
- Stakeholder Satisfaction: Positive feedback from business and technical stakeholders on data accessibility, reliability, usability and delivery support.
- Compliance & Security: No critical incidents related to data governance, privacy or security breaches.
You are Energized by
Contribute to SEAA’s long term ambition and transformation:
- Making an Impact: Seeing how trusted data products directly improve business decisions, client experiences and divisional performance.
- Bridging Business and Analytics: Translating complex data topics into practical decisions and clear stories for non-technical stakeholders.
- Building Trust in Data: Helping the organization align on definitions, improve data quality and use one trusted version of the truth.
- Shaping Data Products: Turning raw requirements into useful dashboards, datasets and analytical products that business users can confidently adopt.
- Collaboration: Working cross-functionally with business, corporate functions, Market Digital Solution, BI, engineering and analytics teams.
What You Will Bring - Capability Requirements
• Business Acumen & Entrepreneurial Mindset: Able to proactively identify data opportunities and use cases that create business value, evaluate initiatives based on impact, strategic alignment, feasibility and resource constraints, and translate them into practical actions that support growth.
• Business Analysis & Requirements Translation:Strong ability to engage stakeholders, clarify ambiguous needs and translate business objectives into structured requirements for BI designers, data engineers and analytics teams.
• Data Product Ownership: Experience managing dashboards, datasets or analytical products through the full lifecycle, including prioritization, delivery coordination, user feedback and continuous improvement.
• Data Stewardship & KPI Management: Strong understanding of data definitions, metric logic, business rules, data ownership and data quality management. Able to facilitate stewardship of key data assets without creating unnecessary governance burden.
• Data Quality & Corporate Data Understanding: Able to assess whether division and corporate data assets, such as HR and finance data, are complete, reliable and fit for the intended business use.
• Operational & Workflow Management: Skilled in coordinating work across business, BI, data engineering and analytics teams, managing competing requests and ensuring timely delivery of data solutions.
• Stakeholder Management & Communication: Able to bridge business and technical perspectives, communicate complex data topics in accessible language and manage expectations across senior and working-level stakeholders.
• Documentation & Data Literacy Enablement: Disciplined in maintaining documentation of data sources, definitions, ownership and key business logic. Comfortable enabling users to understand, interpret and adopt data products.
• Power BI & Data Model Literacy (Good to have): Hands on experience of Power BI, Power Query, DAX and Microsoft Fabric is a plus as the regional data capability evolves.
At Chanel, we are focused on creating an inclusive culture that nurtures personal growth, contributing to collective progress. We believe the uniqueness of each individual increases the diversity, complementarity and effectiveness of our teams. We strongly encourage your application, as we value the perspective, experience and potential you could bring to Chanel.