-Drive the adoption of data profiling and monitoring capability across AME, engage with markets, GBGIs and IT to onboard DQ profiling and DQ monitoring​

-Define meaningful DQ rules and ensure they are fulfilling Reg requirements and fit for purpose

-Design an operating model so that there is clear ownership of the rules, ongoing submission and monitoring.

-Participate in the design of the Group Data Quality Monitoring Tool, championing the specific needs of AME.

-Serve as the DQ contact for markets and businesses in AME supporting the AME DQ Lead, acting as the subject matter expert supporting the region.

-Design and deliver effective and actionable insights on data quality monitoring status and risk in AME, proactively identify opportunities to reduce risk through timely remediation.

-Develop effective relationships with Group Design and Tooling teams, and Cluster Market Heads of Data, Business owners, GBGIs and ITSOs to ensure data quality risk is understood and managed.

-Understand the regulatory landscape relating to data quality management across Asia

-Closely follow up with remediation team when monitoring failed ​

-Perform analysis to constantly provide suggestions to improve data quality in AME

-Assist markets in onboarding DQ Hub

-Knowledge of Data Management principles and understanding of risk management framework, especially regarding data quality

-Understanding of data dictionaries, physical database modelling principles

-Strong analytical skills, proficiency in statical methods and data profiling / validation techniques​

-Experience with visualization of data models and business intelligence tool such as Tableau, PowerBI

-Experience in managing and joining large datasets for analysis, aggregation and reporting

-Experience with data management tools, preferably Collibra

-Hands-on skill on data waggling / ETL tool. Knowing of Alteryx/Python is a definite Advantage

-Preferred experience with Relational Databases, Cloud Technologies, UNIX along with an understanding of modern programming languages

-Preferred experience with conceptual data modelling, business data ontology modelling

-Familiarity with business terminology

-Business process analysis skills.

-Good knowledge in organizational change framework and practices, agile management skills with JIRA

-Proven ability to work in large, complex organizations delivering cross entity/ Regional/ Global changes.

-Attention to detail, strong focus on identifying discrepancies and abnormalities in data, capable of formulating data quality requirement into DQ rules​

-Strong interpersonal skills – ability to work across organizations at all levels

-Strong communications skills – ability to clearly articulate or document current state and recommendations.