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Data Governance Manager

salary Salary :

$40,000 - 50,000 monthly

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Number of Applicants

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000+

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Job Description - Data Governance Manager

Data Quality & Governance Analyst ( Cantonese Speaking)

Banking / Financial Services

We are looking for a Data Quality & Governance Analyst to join a growing data team within a leading financial services organisation. This role has a strong focus on data quality management, ensuring accuracy, integrity, and reliability of data across key business functions.

What you'll be doing:

  • Support the implementation and enhancement of data quality frameworks, including data profiling, validation rules, monitoring, and issue tracking
  • Work closely with business and technology teams to identify data quality issues, perform root cause analysis, and support remediation
  • Use Informatica for data quality monitoring, profiling, and governance activities
  • Track and report data quality metrics (KPIs) and contribute to continuous improvement initiatives
  • Support data governance practices such as data lineage, ownership, and metadata management
  • Assist in preparing documentation for regulatory, audit, and internal control requirements
  • Collaborate with regional teams (including China) on data quality and governance initiatives
  • (Nice to have) Exposure to AI / model governance or data used in AI-related projects

What we're looking for:

  • 3-5 years of experience in data quality management within banking or financial services (MUST)
  • Hands-on experience in data profiling, data validation, issue tracking, and remediation (MUST)
  • Experience using Informatica or similar data quality tools
  • Good understanding of end-to-end data flows and data lifecycle
  • Ability to analyse data issues and communicate findings clearly to stakeholders
  • Strong communication skills - able to present and explain data concepts/tools to both business and technical teams
  • Experience working with cross-functional and regional teams
  • Exposure to data governance (e.g. lineage, ownership, controls) is a plus
  • Exposure to AI governance / model risk / data for AI is an advantage
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