SVP Head, Data Services and Analytics

Lead the Bank's data strategy, analytics, and AI enablement initiatives.

• Key Responsibilities
• Act as the key liaison between business units and technology teams to translate business needs into effective data solutions.
• Lead the planning, implementation, and ongoing enhancement of enterprise data services and platforms.
• Drive the adoption of Data-as-a-Service (DaaS) capabilities to support analytics, AI initiatives, and business innovation.
• Manage end-to-end data projects, including requirements gathering, data onboarding, data mapping, testing, deployment, and post-implementation review.
• Oversee the design, development, and maintenance of data marts, data warehouses, and data lake environments.
• Build and optimise scalable data pipelines that ensure timely, reliable, and secure data delivery.
• Partner with business stakeholders to identify opportunities through data analysis, customer insights, and performance reporting.
• Develop data models, customer segmentation frameworks, and data tagging methodologies using both internal and external data sources.
• Enable business users through self-service analytics tools, dashboards, and reporting solutions.
• Deliver high-quality management information, analytics, and actionable insights to support business and marketing initiatives.
• Collaborate with AI and technology teams to establish and maintain trusted, "AI-ready" datasets.
• Ensure data assets are governed, accessible, accurate, and aligned with enterprise standards.
• Lead, coach, and develop a team of data professionals, fostering a culture of innovation, excellence, and continuous improvement.
• Requirements
• Bachelor's degree or above in Computer Science, Data Science, Statistics, Information Systems, Decision Sciences, or a related discipline.
• At least 10 years of experience in data management, business intelligence, analytics, data warehousing, or related fields within the banking or financial services industry.
• Minimum 3 years of management experience leading data, analytics, or technology teams.
• Strong understanding of banking data domains, data governance, and regulatory requirements.
• Proven experience delivering large-scale enterprise data initiatives from strategy through implementation.
• Hands-on knowledge of data engineering, ETL development, data integration, and data mart design.
• Experience with modern data platforms, cloud technologies, and data architecture frameworks.
• Familiarity with data orchestration and transformation tools such as Airflow, DBT, or similar technologies.
• Experience working with real-time or streaming data technologies, such as Kafka or equivalent platforms.
• Strong expertise in business intelligence and data visualization tools, including Tableau, Power BI, or similar solutions.
• Practical experience in cloud environments such as AWS, Google Cloud Platform (GCP), or Microsoft Azure.
• Strong analytical, problem-solving, and stakeholder management skills.
• Demonstrated ability to manage multiple priorities and deliver results in a fast-paced environment.
• Excellent communication and influencing skills, with the ability to engage both technical and non-technical audiences.
• Business-minded, collaborative, and customer-focused.
• Proficiency in written and spoken English and Chinese, including Cantonese and Mandarin.