Senior VP, Data Products Lead, Innovation Group

UOB; Singapore; On-site; SGD 220,000 - 300,000; Full time

Job summary

1011 United Overseas Bank Ltd in Singapore is seeking a senior data products leader to define and drive the enterprise data products roadmap. You will govern data product lifecycles, promote a product-led mindset, and collaborate across business units to deliver scalable, governed data solutions.

Lead a cross-functional team to publish high-quality datasets and data products for analytics and decision-making, ensuring security, access controls, and adoption.

Qualifications

• 12+ years of experience in enterprise data applications, data transformation, data products, analytics enablement, or related leadership roles.
• Proven track record leading enterprise-scale data initiatives in banking, financial services, or a regulated environment.
• Strong experience building or scaling data products, Data-as-a-Service capabilities, self-service data platforms, data discovery services.

Responsibilities

• Set the enterprise vision, strategy, and roadmap for Data Products and Data-as-a-Service.
• Define the data product operating model, lifecycle, governance, and value measurement.
• Lead the enterprise data enablement shopfront with data services, training, advisory, and user support.

Skills

Enterprise data products

Data governance

Leadership

Stakeholder management

Product strategy

Education

Bachelor/Master in relevant field

Tools

Data platforms

Analytics tools

Job description

Company: 1011 United Overseas Bank Ltd

About UOB

United Overseas Bank Limited (UOB) is a leading bank in Asia with a global network of more than 500 branches and offices in 19 countries and territories in Asia Pacific, Europe and North America. In Asia, we operate through our head office in Singapore and banking subsidiaries in China, Indonesia, Malaysia and Thailand, as well as branches and offices. Our history spans more than 80 years. Over this time, we have been guided by our values – Honorable, Enterprising, United and Committed. This means we always strive to do what is right, build for the future, work as one team and pursue long-term success. It is how we work, consistently, be it towards the company, our colleagues or our customers.

Job Description

Key Responsibilities

Enterprise Data Products and Data-as-a-Service Strategy

• Set the enterprise vision, strategy, and roadmap for Data Products and Data-as-a-Service, aligned to business priorities, analytics, AI, digital transformation, and regulatory expectations.
• Define the data product operating model, including product ownership, lifecycle management,prioritisation, governance, delivery standards, service model, and value measurement.
• Shape andprioritisehigh-value data product use cases with business units, ensuring every priority use case is linked to a clear business owner, consumption pathway, value hypothesis, and measurable outcome.
• Promote a product-led mindset across enterprise data delivery, shifting theorganisationfrom project-by-project data extraction to reusable, governed, and scalable data products.
• Lead the enterprise data enablement shopfront, providing data services, training, advisory, and user support to make enterprise data easier to find, understand, access, and consume.

Data Product Delivery, Engineering andOperationalisation

• Oversee the engineering, curation, and publication of high-quality datasets and data products for reporting, analytics, and business decisioning.
• Guidethe development of enterprise data models, common definitions, reusable patterns, and controlled data assets to improve consistency, scale, and interoperability across the bank.
• Operationalisedata product applications and self-service consumption channels for business units, ensuring usability, reliability, governance, access controls, and adoption are embedded from day one.
• Partner with technology and platform teams to ensure data products are production-grade, secure,monitored, well-documented, and aligned to enterprise architecture standards.
• Provide end-to-end data support for strategic initiatives and Innovation Challenge use cases, enabling experimentation while ensuring solutions can scale safely into enterprise adoption.

Data Adoption,Monetisationand Business ValueRealisation

• Partner with business units toidentifyand shape datamonetisationopportunities, including revenue growth, customer experience, productivity, risk reduction, operational efficiency, and decision quality use cases.
• Define adoption pathways for data products, including stakeholder engagement, product education, training, communication, change management, and success measurement.
• Establish value tracking disciplines for data products, including usage growth, active consumers, business benefits, turnaround-time reduction, risk outcomes, and reuse indicators.
• Translate technical data capabilities into business narratives that senior stakeholders can understand, sponsor, and act upon.
• Champion data literacy and capability uplift through structured training, playbooks, communities of practice, and reusabledeliveryassets.

Centre of Excellence, Delivery Discipline and Capability Building

• Establish and lead a Data Products Centre of Excellence to provide advisory, reusable playbooks, standards, delivery support, adoption frameworks, and governance guidance for enterprise data initiatives.
• Create repeatable methods for use case intake,prioritisation, discovery, business case development, product design, data readiness,operationalisation, and benefits tracking.
• Strengthen delivery discipline across data projects by embedding clear ownership, milestones, risk reviews, dependency management, stakeholder routines, and measurable outcomes.
• Build a high-performing multidisciplinary team across data product management, data engineering enablement, service management, governance, and business adoption.
• Foster a culture of customer-centricity, accountability, innovation, reuse, risk awareness, and continuous improvement.

Governance, Risk and Controls

• Embed governance, access management, risk assessment, monitoring, and control requirementsintodata products, data services, and data discovery capabilities.
• Ensure enterprise data consumption is safe, auditable, well-controlled, and aligned to regulatory expectations for a banking environment.
• Partner with Risk, Compliance, Security, Legal, Technology, and Data Governance teams to strengthen control design, risk monitoring, issue management, and operational discipline.
• Oversee reviews of data usage, user access, service exceptions, control gaps, and remediation actions tominimiseoperational, regulatory, and data risks.
• Balance speed-to-value with strong governance, ensuring data transformation outcomes are scalable, trusted, and sustainable.

Key Skills & Experience

Mandatory Experience

• 12+ years of experience in enterprise data applications, data transformation, data products, analytics enablement, enterprise platforms, or related leadership roles.
• Proventrack recordleading enterprise-scale data initiatives in banking, financial services, or another complex regulated environment.
• Strong experience building or scaling data products, Data-as-a-Service capabilities, self-service data platforms, data discovery services, or enterprise analytics enablement functions.
• Demonstrated ability to partner with senior business stakeholders to shape demand, define value cases,prioritiseuse cases, and drive measurable outcomes.
• Strong understanding of data governance, data quality, metadata, lineage, access controls, data risk management, and operational controls.
• Proven leadership of cross-functional teams across business, data, technology, governance, and risk domains.
• Excellent executive communication skills, with the ability to simplify complex data topics and influence decision-making at senior levels.

Preferred Experience

• Experienceestablishinga Data Productsorganisation, Data ProductCoE, data marketplace, enterprise data catalogue, data discovery platform, orgovernedself-service data capability.
• Exposure to AI, advanced analytics, machine learning, customer analytics, risk analytics, regulatory reporting, or digital banking use cases.
• Experience with modern data ecosystems, including cloud data platforms, data lakes, data warehouses, data catalogues, API-based data services, and analytics tools.
• Familiarity with product management practices, agile delivery, service management, change adoption, and benefitsrealisationframeworks.