Key Responsibilities
Requirements
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV.
- 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.
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV.
Job ID 1289756
Hays Hong Kong Limited ("Hays Hong Kong") is the one of the leading specialist recruitment companies in Hong Kong in recruiting qualified, professiona...
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