Data Product Lead — Enterprise Platform & Governance

Global Sports Jobs Limited

Hong Kong

On-site

HKD 900,000 - 1,500,000

Full time

14 days+

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Benefits offered by this job

Competitive salary

Development opportunities

Job summary

The Hong Kong Jockey Club's Membership and Customer Excellence (MCE) Division leads the club's data strategy and delivers enterprise data products across digital and physical touchpoints. The role acts as the bridge between business stakeholders and technology teams, shaping roadmaps, user stories and delivery plans while ensuring governance and measurable business value.

You'll collaborate with business units, data scientists and IT to enable analytics, AI, reporting and operational use cases,

Qualifications

Bachelor's degree in Business Analytics, Information Systems, Computer Science, Engineering, Data Science or related disciplines.
At least 8-10 years of experience in data management, data products, business analysis, analytics delivery, data platform implementation or related disciplines.
Experience in delivering, implementing or managing enterprise data platforms, data products and data-driven solutions.
Strong understanding of enterprise data platforms, data architecture, data integration and data governance principles.
Experience supporting analytics, AI, reporting and data-driven decision-making initiatives in an enterprise environment.
Familiarity with cloud-based data platforms, data services and modern data technologies.
Strong business analysis, problem-solving, facilitation and communication skills.
Demonstrated ability to work effectively with cross-functional stakeholders across business and technology teams in a complex organisational environment.
Proven experience in translating business requirements into data products, analytics solutions and data-driven capabilities.
Strong experience in stakeholder engagement and working with business and technology teams to define priorities, requirements and delivery outcomes.

Responsibilities

Drive the development and implementation of enterprise data products by partnering with business stakeholders to identify opportunities, define requirements and prioritise initiatives that deliver measurable business value.
Act as the primary bridge between business and technology teams, translating business objectives, processes and requirements into data product roadmaps, user stories and actionable delivery plans.
Lead the end-to-end delivery of data products and platform capabilities, ensuring solutions align with enterprise data strategy, governance standards and business outcomes.
Collaborate with business units, solution teams, data scientists and IT teams to enable analytics, AI, reporting and operational use cases through trusted and accessible data assets.
Define and manage data product requirements, backlog priorities, acceptance criteria and success measures, and maintain business and functional documentation such as product requirements, data definitions and process flows.
Promote the use and adoption of the enterprise data platform and data products through stakeholder engagement, training, communication and change management activities.
Ensure data is structured, accessible, reusable and appropriately governed through effective data definitions, metadata management, data quality controls and business data standards, and ensure compliance with data governance, security, privacy and risk management requirements.
Support the delivery and continuous enhancement of the enterprise data platform roadmap by identifying business needs, capability gaps and improvement opportunities
Working closely with IT and platform engineering teams so that platform capabilities support evolving business requirements and strategic priorities.
Support vendor management and technology delivery activities, ensuring solutions meet business requirements, quality standards and expected outcomes.
Monitor adoption, utilisation, business benefits and performance of data products and recommend enhancements to maximise value and user experience.
Support cost, capacity and investment optimisation by assessing platform utilisation trends and recommending improvement opportunities.
Continuously identify emerging technologies, data capabilities and industry best practices that can enhance business outcomes and accelerate data-driven innovation.