Data Products & Stewardship Manager, Corporate, SEAA

Chanel Pte Limited; Singapore; On-site; SGD 150,000 - 180,000; Full time

Job summary

Chanel Pte Limited seeks a Data Products & Stewardship Manager to manage lifecycle of data products, dashboards, reports and AI-enabled products. You will partner with business and data delivery teams to identify opportunities, define data requirements and ensure trusted data sources.

You will drive data quality, governance frameworks, and adoption of self-service analytics across SEAA to accelerate LEAP ambition and business value.

Qualifications

• Ability to drive data stewardship and governance across multiple regions.
• Ability to define data definitions, business logic and data quality standards.
• Proven stakeholder management across divisions and corporate functions.

Responsibilities

• Act as primary facilitator of data stewardship practices across SEAA.
• Define scope of data under governance for Critical Data Elements.
• Ensure standards and policies for data definitions, resolve data quality issues.
• Lead lifecycle of divison/function data products from ideation to adoption.
• Own the product backlog and coordinate data/BI engineering workflows.
• Drive adoption of data products and self-service analytics.

Skills

Data stewardship

Data governance

Stakeholder management

Data quality

Power BI

Tools

Power BI

Power Query

DAX

Job description

The Data Products & Stewardship Manageris responsible formanaging the lifecycle of division and function data products, including dashboards, reports,datasetsand future AI-enabled data products - fromideation through delivery,adoptionand continuous improvement. The role acts as a bridge between division and function stakeholders and data delivery teams, working closely with the business to proactivelyidentifyopportunities 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 CreateInTheRole:

Data Stewardship and Governance Facilitation:

• Act as the primary facilitator of data stewardship practices across SEAA, driving alignment on data definitions, businesslogicand 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 tovalidatedefinitions and resolve data quality issues.

• Drive the adoption of data stewardship practices across business teams by embedding clear frameworks,toolsand ways of working into day-to-day operations, ensuring governance is applied consistently without creating unnecessary complexity

Data Quality Management:

• Work with business stakeholders toidentifyandfacilitatethe production of Data Quality Rules and Data Quality Reporting.

• Identifyprocesses 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 toidentifyhigh-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 togather, clarify, and prioritize data requirements and need.

• Oversee thelifecycle 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 businessdecision-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, ensuringtimelyandaccuratedelivery of data solutions.

Business partnership and product adoption:

• Ensure business requirements are clear,granularand 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 ofa single sourceof truth.

Continuous Improvement:

• Identifyopportunities 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 levelsof accuracy, completeness,consistencyand usability aremaintainedacross division data and relevant corporate data assets.

• Adoption & Usage:Increased usage of dashboards,datasetsand data products by target business users.

• Requirement Readiness:Business requirements are clear,granularand ready for BI,engineeringand analytics teams to deliver with minimal rework.

• Prioritization Discipline: Theproduct backlog is actively managed, with clear rationale for what is prioritized,phasedor declined-ensuring team capacity is focused on highest-value outcomes.

• Issue Resolution:Data-related issues areidentified,escalatedand resolvedin a timely manner.

• Stakeholder Satisfaction:Positive feedback from business and technical stakeholders on data accessibility, reliability,usabilityand delivery support.

• Compliance & Security:No critical incidents related to data governance,privacyor security breaches.

You are Energized by

Contributing to SEAA’s long term ambition and transformation:

• Making an Impact:Seeing how trusted data products directly improve business decisions, clientexperiencesand 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 organizationalign ondefinitions,improvedataqualityanduseone trusted version of the truth.

• Shaping Data Products:Turning raw requirements into useful dashboards,datasetsand analytical products that business users can confidently adopt.

• Collaboration:Working cross-functionallywith business, corporate functions, Market Digital Solution, BI,engineeringand analytics teams.

What You Will Bring - CapabilityRequirements

Business Acumen & Entrepreneurial Mindset:Able to proactivelyidentifydata opportunities and use cases that create business value, evaluate initiatives based on impact, strategic alignment,feasibilityand resource constraints, and translate them into practical actions that support growth.

Business Analysis & RequirementsTranslation:Strongability to engage stakeholders, clarify ambiguous needs and translate businessobjectivesinto structured requirements for BI designers, dataengineersand analytics teams.

Data Product Ownership:Experience managing dashboards,datasetsor analytical products through the full lifecycle, including prioritization, delivery coordination, userfeedbackand continuous improvement.

Data Stewardship & KPI Management:Strong understanding of data definitions, metric logic, business rules, dataownershipand data quality management. Able tofacilitatestewardship 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,reliableand 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 ensuringtimelydelivery 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 inmaintainingdocumentation of data sources, definitions,ownershipand 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,DAXand Microsoft Fabric is a plus as the regional data capability evolves.