Systems Analyst (Data Warehouse) (ITO)

Founded in 1989, Hong Kong Metropolitan University (HKMU) is a modern, vibrant and dynamic university. We tailor our professional programmes to adapt to market trends and meet industry needs, thus providing our students with quality professional education and clear career paths. Being the first University of Applied Sciences (UAS) in Hong Kong, we pledge to play a pioneering role in enhancing recognition of vocational and professional education and training, and nurturing talents with both applied skills and knowledge.

As a faculty-driven, student-centred university in support of innovative teaching and learning, strategic research, and stakeholder outreach to provide maximum benefit to our communities, we conduct research that advances knowledge and enhances teaching, focusing on strategic areas, including digital humanities and literature, international business, gerontechnology, personalised care, smart city, open and innovative education, and bilingual learning and teaching.

HKMU is becoming an ever more vital link in addressing and helping Hong Kong to solve many difficult challenges – as part of our involvement in, and commitment to, the ‘metropolis’ of Hong Kong. Our plans to expand into the Greater Bay Area (GBA) will also cultivate talent to serve Hong Kong and the wider metropolitan GBA.

For more information about the University, please visit https://www.hkmu.edu.hk.

We are now looking for a suitable person to fill the following position in the Information Technology Office:

Major Duties and Responsibilities The appointee will be responsible mainly for the following:

• Designing and building end-to-end data pipelines, including data collection, transformation, and integration;

• Implementing and fine-tuning AI-driven data analytics solutions;

• Leveraging AI products to enhance the efficiency and productivity of solutions;

• Developing and managing a wide range of data sets to support analytic tools;

• Establishing and maintaining data quality standards, and ensuring compliance with University policies on data protection and information security; and

• Performing any other duties as assigned.

Candidates

Candidates should possess the following qualifications, experience and competence:

• Candidates should possess the following qualifications, experience and competence:

• A recognised degree in Computer Science/Information Technology or related disciplines;

• At least 3 years' relevant post-qualification experience, preferably with exposure in Oracle/MSSQL Database, AI Model Integration Techniques, ETL Processing and Methodologies;

• Solid hands-on experience with :

• Reporting and business intelligence (BI) Tools (e.g. Power BI, Tableau, SSRS etc);

• ETL/ELT tools, SQL and data analytics (e.g. Alteryx, PL/SQL, T-SQL, SSIS etc);

• Row-level Security and secure data access design;

• Microsoft Fabric IQ, Fabric Data/AI tools, or other cloud data platform;

• Solid experience in implementing data warehouse solutions, preferably in higher education; and

• A keen interest in the latest generative AI developments and a passion for innovation.

Candidates may be invited to attend a written test.

Terms and Conditions for Appointment

An attractive remuneration package, including basic salary, an end-of-contract gratuity, and a discretionary incentive payment, where applicable, will be offered to the right candidates. Generous annual leave, staff-development sponsorships, medical and dental benefits, and life insurance coverage will also be provided.

To Apply

Candidates who are interested in joining us may submit their applications via the University’s eRecruitment System.

The personal data collected will be used for the purpose of considering your application for employment. For details, please refer to the “Personal Data (Privacy) Notice for Job Applicant” on the University’s website. If you are not contacted by the University within eight weeks from the closing date of application, you may assume that your application was unsuccessful. The University will continue to review applications until the position(s) is/are filled.