Manager, Data Quality and Governance

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About the role:

This position will be responsible for data governance support for all current and future business line data governance for WD to enable the business to understand, access, trust and properly protect the data. This is a global role that could reside in the AM region (any city in the US), the EMEA region (based in JLL’s Warsaw office or London office) or the APAC regions (based in JLL’s Singapore office) with the flexibility to travel up to 15%, including international travel.

This position will report to the head of Enterprise Data Governance of the CDO’s organization in JLLT. It is a lead role that will support the prioritization and planning of WD data needs.  He or she will also be the point of contact for WD management for all data governance topics.
The Data Ownership & Lifecycle Management Lead will be responsible for providing consultation and guidance for his/ her peers to ensure cohesion and clarity of WD business requirements and objectives for data.  She or he will work closely with the data governance leaders assigned to various regions, business lines, operations, markets and client accounts to understand best practices, JLL data standards and policies, and the data quality needs.

Responsibilities:

• Lead the WD Data Governance function. Partner with WD Global Operations teams, the JLLT product support, particularly the transition teams for new client accounts, and the client account teams to rationalize the business contexts (trends and business strategy) and their needs for data governance.

• As part of the WD Global Data Governance organization, lead the global Data Governance function in all regions. Partner with WD Global Operations teams, the markets and the client account teams to rationalize the business contexts (trends and business strategy) and their needs for data governance.

• Responsible for the WD Data Governance strategy, including data quality management, data standard compliance, master data management, and data for business intelligence. Develop expert business knowledge and solutions in the above areas of focus.

• Drive the adoption of the central data quality monitoring and remediation program including the LightHouse platform and operations, a home-grown product for data quality deployed to multiple clients and operation teams.

• For the adoption of RED (or Azara) Platform, facilitate meetings with account executives, data stewards, and other stakeholders to ensure data governance processes and standards are enforced. Guide the client account teams to establish data governance on each account.

• Direct continuous improvement of data management practices to ensure that data sources are documented, understandable, accessible, and secure. Develop a strategy to specify data validation, verification and reconciliation strategies based on data classes across its lifecycle.

• Identify and prioritize data integration opportunities and propose solutions. Partner with IT to identify and implement best practices, tools and standards for data governance/ data quality improvement.

• Establish service level management, aligning the data and analytics resources on different teams based on business expectations for performance, availability, data quality and relevance.

• Follow the guidance from WD Global Data Governance and global-regional IT organizations to adopt and leverage common best practices and standard frameworks, tools and processes. Implement checkpoint reviews and periodic audits to ensure the data artifacts are governed properly following the Global Data Governance guidance across the WD business.

• Develop and maintain Data Governance policies, processes and standards at various levels, i.e. region, market, client account team, etc.

• Define and maintain Data Governance compliance and operational metrics, prepare reports and metrics, execute audits and collaborate with the stakeholders to resolve data issues.

• Leverage the WD data stewardship program to resolve data quality and data governance compliance issues.

• Identify areas for improvement and makes training recommendations for data governan