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Citi is committed to achieving and maintaining high quality data and to enabling Citi to continue to operate in a safe and sound manner. Data lies at the core of the business and it is a critical asset underlying Citi's businesses and strategic decisions.
As a Global Systemically Important Bank and a Domestic Systemically Important Bank in various jurisdictions, Citi must comply with regulatory requirements and expectations related to sound data management practices such as, but not limited to, the Office of the Comptroller of the Currency (OCC) Heightened Standards (12 CFR Part 30, Principles for Effective Risk Data Aggregation and Reporting (Basel Committee on Banking Supervision (BCBS 239)), Anti-Money Laundering (AML) and other applicable regulatory guidance.
Citi's Data Strategy is focused on building a business data architecture, a Data Quality framework and a systems infrastructure that generate accurate, complete, and timely information in the form of Key Reports (risk, financial, regulatory and management reports) to enable decisions during business-as-usual operations and ad hoc analysis in times of stress.
Having good quality data enables us to drive our business and, more importantly, deliver the best for our clients. To support this need, Citi has launched the Data Quality Program to enhance Citi's approach to Data ownership, culture, quality and architecture and implement Citi's strategy for Data Architecture and System Infrastructure.
Refreshed annually, the Citi Data Management Policy (CDMP) underwent a major change to support the Data Quality Program, representing the implementation of Citi's data strategy for risk management and regulatory and financial information, meeting Management and Board expectations for supervisory standards. It sets the framework to improve the data architecture, data quality framework, and systems infrastructure to generate accurate, complete, and timely information and reports.
As part of the new operating model with new roles and responsibilities introduced in the CDMP, the Regional Data Steward function is a strategic role that is responsible for establishing and executing a robust and regionally consistent Data Stewardship framework and activities that addresses the multi-jurisdictional regulatory complexities with a high level of standardization across Asia and EMEA and instituting a rigorous governance and oversight process across 17 countries in Asia and EMEA, in partnership with the Business Process Owners (e.g., system lineage, mapping data elements and concepts, maintenance of data quality rules and controls).
This role reports to the Asia/ EMEA Regional AML/FATCA Controls CBORC Head.
The Regional Consumer Data Steward is responsible for mapping processes at the level 3 process taxonomy while maintaining accurate mapping, list of data domains, contents, and data elements in process following adjustments and data-related changes, with additional responsibilities of maintaining data quality rules and controls, identifying and remediating quality issues within their business processes or data domains.
At a regional level, the incumbent will identify Trusted Sources for each Critical Data Element (CDE), implement and maintain appropriate Data Quality rules and controls for Corporate CDEs and CDEs inline with the Citi Data Management Policy. As a skilled data professional, the role will play a vital role in the identification and remediation of Data Quality issues within the Consumer Business Process; coordinating with stakeholders on issue resolution, prioritizing issues, providing support for both tactical and strategic remediation and monitoring resolution. The incumbent will also document and maintain the system lineage, and map data to the logical data model (where applicable), develop and maintain the Business Glossary, in addition to maintaining the quality and timeliness of data feeding Trusted Sources.
A shortlist of the key Data Stewardship activities include:
Partner closely with Process Owner on Data Quality and process activities
Identify and raise Data Quality issues within Asia/EMEA GCB Products and processes
Facilitate status meetings on open Data Quality exceptions / issues relating to a process and lead remediation efforts
Establish and publish Data Quality metrics and scorecards to support Process Owner
Coordinate with the Process Owner to review process maps including Data Domains, Data Concepts and Data Elements and make updates to account for changes (e.g., business or regulatory driven changes)
Coordinate with Technology and Data Custodians to ensure that the Data Lineage toolset is working as intended, including managing technical metadata and coordinating Data Lineage tasks and testing activities
Identify required changes to metadata and make required updates
Perform Data Profiling with support from the Data Custodian, review and analyze Data Profiling results for Corporate CDEs and CDEs
Determine and implement Data Quality rules, in collaboration with Business Architects by Data Domain and Data Custodians
Support Data Custodian with review and update to Data Dictionaries
Collaborate with Process Owners to ensure that appropriate Data Quality rules and controls are in place within their processes (including for Corporate CDEs and CDEs)
Ensure changes are appropriately communicated to the CDEs to Data Providers, with support from Business Architects by Data Domain
Facilitate meetings with the Process Owner, Business Architects by Data Domain and Data Providers to review the appropriateness of Trusted Source assignment for CDEs in their Product, Process or Region
Develop the Business Glossary and system lineage related to the process, and review with the Process Owner
Work with the Process Owners to ensure the appropriate individuals are mapped to their process
Establish and Implement Business and Data Architecture Standard/ Requirements
Work with the Business Architect to map/ link the Data Domains and Data Concept(s) to Data Source(s), and identify the System of Origin, System of Record, and Authoritative Provisioning Point, as applicable.
Manage identified and defined Data Concept and Data Element values that are inputs and outputs supporting business processes and process functions
Support Data Custodian with review and update to Data Dictionaries
Support the Process Owners to manage restrictions on data access and use by the business processes and process functions
Support the Process Owners to identify root cause and resolve data issues
Establish and Implement Data Quality Management Standard
Data Profiling - Perform Data Profiling with support from the Data Custodian and review Data Profiling results for Corporate CDEs and CDEs
Data Quality Controls - Assess data at each stage of the data lifecycle for the four control principles of Accuracy, Comprehensiveness, Timeliness, and Consistency. Each control principle is comprised of Data Quality dimensions detailed in the Data Quality Management process documents.
Data Quality Issue Management - Collaborate with Business Process Owners, Data Custodians and Business Architects by Data Domain for issue remediation, evaluate and identify material and persistent Data Quality exceptions for remediation via the Data Quality Exceptions and Issue Management and Resolution processes, in line with the Data Quality Exceptions Procedures and IMR Standard Operating Procedures Guide.
Data Quality Management Strategy - Work with Business Process Owners to define and implement the data quality management strategy for maintaining data quality
Data Quality Rules - Work with Business Process Owners to define, document, and maintain Data Quality rules for Corporate CDEs based on 'Fit for Purpose' requirements pertinent for the Business/Global Function process by leveraging technology enabled by the CDO. Collaborate with Data Custodians to implement standards and Data Quality rules at appropriate points of measurement.
Detective Data Quality Controls - Coordinate with the Business Process Owners and Data Custodians to develop and implement Detective Data Quality Controls covering Scorecards, Data Quality Exceptions and Data Tracing. Review Data Quality exceptions including material and persistent Data Quality exceptions to ensure that they have been actioned through a Data Quality corrective action approach (i.e. Data Quality Exceptions, Issue Management and Resolution)
Preventive Data Quality Controls - Implement and maintain Preventive Data Quality controls to ensure data is captured correctly (e.g. maker/checker, data entry validation) with support from Data Custodians, and ensure the adoption of Data Quality Control principles for implementation of Preventative Controls and Detective Controls
Establish and Implement Metadata Standard
Critical Data Elements (CDEs) - Identify and propose Data Elements from the Business Processes that must be designated as Critical, with support from Process Owners and Data Custodians
Maintenance and Monitoring - Review the changes to data lineage in partnership with Data Custodians and Business Process Owners and communicate these changes to the applicable DGO and CDO, consult Data Providers to determine if the proposed change(s) will have any adverse consequences and check that rules are adhered to (such as mandatory fields being populated, any other rules and restrictions are adhered to, etc.), and identify required changes to metadata and notify the Business Architects by Data Domain for review, approval and update in the Metadata Repositories
Metadata Captured in the Business Architecture Business Process - Work with Business Process to capture and maintain the metadata which will be stored in accordance with the CDO's metadata management process document
Metadata: Data Lineage - Coordinate with Technology and Data Custodians to ensure that the Data Lineage toolset is working as intended, including managing technical metadata and coordinating Data Lineage tasks and testing activities
Metadata: Trusted Sources - Review any discrepancies identified by the CDO and follow mitigation strategies to remediate the impacted data sources with support from Data Custodian.
Change Management (Data Governance Model) - Collaborate with Data Custodian, Process Owners and Technology to fully execute required change management procedures
Data Stewardship Model - Engage with other stakeholders, such as Data Custodians, Data Providers, and Process Owners, for ongoing alignment on data-related decisions.
University graduate with at least 15 years of experience with strong strategic and analytical skills
Good working knowledge of Citi's Data Strategy and data quality requirements and understanding of metadata, with prior experience in implementing and maintaining Data Quality rules and controls
Strong ability to understand the purpose of Products and processes in terms of the greater context of the business, what data is being captured and experience in coordinating with stakeholders to drive changes relating to issue resolution, controls and Data Quality
Good understanding of Citi's technical infrastructure and experience with tools and applications including process mapping and lineage toolsets
Strong ability to understand discrete process steps and data flow, and determine source of remediation to address Data Quality issues
Good understanding of operational risk and control processes and procedures
Strong stakeholder management skills (e.g. written and verbal communication, influencing and negotiation)
Excellent quantitative, analytical and problem solving skills with attention to details
Ability to work independently, interface and execute with a sense of urgency and deliver tasks effectively
Proactive, self-motivated and proven ability to use own initiative and judgment and take lead to work with internal and external clients in a positive manner and help deliver solutions that benefit the business
Proven ability to influence across products and functions and operate effectively at all levels in a collaborative manner
Strong interpersonal skills, situational awareness and emotional intelligence
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