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Jobtailor is seeking a data governance professional to enhance independent data governance and quality assurance across Credit Risk data domains. You will test data quality controls, define and monitor KPIs with Data Owners and Data Stewards, and localise governance artefacts.
The role involves applying BCBS 239/RDARR principles, building inventories, mappings, dictionaries, and reports, plus contributing to audit and assurance activities.
Provide independent data governance and data quality assurance within PPB Credit Risk's Enterprise Risk function as Second Line of Defence (2LOD)
Build and test data quality controls
Support design and implementation of the Data Ownership framework
Work with Data Owners and Data Stewards to define and monitor data quality KPIs
Localise governance policies, standards, and artefacts for the Credit Risk data domain
Apply BCBS 239/RDARR principles to control design across upstream and downstream data flows
Provide input on data governance and control design within projects
Create and maintain Critical Data Element inventories, Source-to-Target Mapping documentation, data dictionaries, and business glossaries
Design, build, and where possible automate data quality controls and validation logic
Perform data integrity gap analysis and coordinate resolution with Data Engineering, IT, and business owners
Build and maintain data quality and governance reporting dashboards
Use AI-enabled data quality tooling to strengthen control coverage and reduce manual effort
Ensure data quality is embedded in new solution and project development
Gather and interpret functional requirements and translate them into governance and reporting solutions
Draft governance documentation and reporting
Maintain evidence trails supporting BCBS 239 self-assessments, attestations, and Issue and Control Process requirements
Support internal and external audit reviews and Combined Assurance activities
Demonstrates expertise in data governance and quality assurance, with a strong focus on BCBS 239 principles and the ability to design and implement effective data quality controls. Proficient in utilizing SQL, SAS, and AI-enabled data quality tools to enhance data integrity and reporting.