Lead Data Product Manager

Executive Summary

• The Role: Lead Data Product Manager (Enterprise Data & AI)
• Seniority / Exp: 12+ years total experience, with 5+ years leading data product, data management, or analytics delivery across multiple domains.
• Core Focus: Building and owning cross-domain, AI-ready data products (semantic layers, data marts, data contracts) that power analytics and AI agents.
• Key Skills Required:
  • Hands-on technical depth: SQL validation, data modeling, requirement writing, and data governance (glossaries, catalogs, lineage).
  • AI literacy: Generative AI, agentic AI, and RAG.
  • Strong Agile product management, leadership, and stakeholder influence without authority.
• Client Environment: Established, large-scale organization in Singapore expanding enterprise data and AI capabilities.

Details

Lead Data Product Manager

About the Client

Our client is an established, large-scale organization in Singapore expanding its enterprise data capabilities and AI adoption.

What You Do

As Lead Data Product Manager, you will lead data products for your assigned business domains. You will partner with business and IT leaders to turn their priorities into trusted, AI-ready data products that power analytics, data agents, and decision-making. You will own the data product roadmap for your domains and deliver cross-domain data products. You will also be hands-on: writing requirements, specifying AI context and signing off data products, while leading Data Product Managers.

Product leadership and partnership

• Own the data product roadmap for your business domains, prioritising across data consumers using the agreed prioritisation framework.
• Partner with functional leads, data stewards, and business leaders, up to senior management level, to align their roadmaps and priorities with the data product roadmap.
• Deliver cross-domain data products, working with delegated data stewards across domains.
• Coordinate data platform, engineering, analytics, and governance teams to deliver data products end to end.
• Manage vendors and procurement where applicable.

AI-ready data products

• Ensure every data product meets the single AI-ready standard: business glossary, semantic layer, data catalogue, lineage and data contract.
• Keep shared measures and dimensions consistent across domains and resolve definition conflicts with data stewards.
• Identify AI use cases and enable data agents, analytics, data science, and downstream applications on your data products.
• Guide complex data product designs, such as master data and cross-domain products.

Hands-on delivery

• Write requirement specs, user stories, and acceptance criteria for data products.
• Specify business glossary terms, semantic layer measures and dimensions, and data catalogue entries for data steward approval.
• Set up data contracts, product quality rules, and SLAs to governance standards.
• Review logical models with data engineers and sign off published tables and columns.
• Prepare data products for AI-ready certification and complete certification checklists.

Domain data depth and storytelling

• Build deep knowledge of your domains' data: source and data product structure, business rules, lineage, and quality.
• Present domain outcomes and value to senior stakeholders, in terms of decisions enabled, time saved and risk reduced.

Who You Are

Must Have

• At least 12 years of experience, including 5 years leading data product, data management or analytics delivery across multiple business domains.
• Proven delivery of data products into production, such as curated data models, semantic layers or data marts used by multiple teams.
• Hands-on experience writing requirements and acceptance criteria, working with data models, and using SQL to validate data.
• Working knowledge of data governance: business glossaries, data catalogues, lineage, data contracts and data quality.
• AI literacy, including generative AI, agentic AI and RAG, with hands-on use of AI-assisted tools to improve delivery and documentation.
• Strong stakeholder management with senior business and technology leaders; able to influence without authority.
• Experience leading a team.
• Experience in Agile product management: roadmap planning, backlog prioritisation and delivery coordination.

Nice to Have

• Experience enabling data agents or AI applications on enterprise data products.
• Experience with Microsoft Fabric or other cloud data platforms.
• Experience with data governance platforms such as OpenMetadata, Microsoft Purview, Collibra or Informatica IDMC.
• Experience in large public sector, MNC, or complex enterprise environments.
• Certified in CSPO, PMP or CITPM; AI or data management certification (e.g. CDMP).

To Apply

Please submit your resume to our recruitment team. We will be in touch with suitable candidates to discuss the opportunity in greater detail.

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