Data Governance Lead

Job Title

Data Governance Lead

Job Description Summary

The Data Governance Lead will establish and operate practical governance across the DNA Data and Analytics portfolio. The role ensures that priority data and analytics products have clear ownership agreed-upon definitions measurable quality traceable lineage appropriate controls and evidence of fitness for purpose. Working with business owners data stewards technology teams analytics teams risk functions and supply partners the Data Governance Lead will translate enterprise requirements into proportionate practices that support trusted decision-making regulatory compliance and AI readiness.

Business and process owners remain accountable for source data accuracy and remediation while the Data and Analytics team provides the governance framework semantic context quality evidence and trusted data consumption layer.

Job Description

Key accountabilities

1. Governance strategy operating model ownership and stewardship

• Define and operate the DNA governance roadmap standards decision rights and proportionate controls aligned with enterprise policy and data risk.

• Establish clear governance roles decision rights and escalation paths across Data Owners Data Stewards Product Owners technology teams analytics teams and supply partners.

• Ensure governance is proportionate to business value data criticality regulatory exposure and delivery risk.

• Maintain a prioritised governance plan with clear milestones dependencies decision points and measures of adoption. Review the plan regularly with DNA leadership and adjust it as business priorities regulatory expectations architecture delivery capacity and data risks change.

• Establish clear Data Owner and Data Steward coverage for priority domains including responsibilities approval rights escalation paths coaching and resolution of ownership gaps.

• Enable owners and stewards to fulfil their responsibilities through practical playbooks role-based guidance decision templates and regular coaching. Monitor coverage and participation identify persistent gaps and escalate where unclear accountability prevents timely approval issue resolution or responsible use of data.
  

2. Semantics metadata critical data and data quality

• Maintain agreed business definitions semantic standards metadata data dictionaries and catalogue records so that priority data products are discoverable understandable traceable and reusable.

• Lead the identification of Critical Data Elements and the lifecycle of business and data-quality rules including agreed dimensions thresholds monitoring root-cause analysis source remediation exception management and escalation.

• Partner with domain experts data engineers analysts and control functions to ensure definitions and quality rules are implementable and consistently interpreted. Use profiling and monitoring results to identify material issues agree remediation ownership and target dates document accepted exceptions and report trends that require management attention.
  

3. Data-quality monitoring lineage controls and governed data products

• Oversee adoption of data-quality monitoring and trust indicators ensuring that rules are linked to approved definitions accountable owners agreed thresholds and remediation actions.

• Ensure that material data flows transformations dependencies controls approvals exceptions and lifecycle decisions are traceable and supported by appropriate evidence.

• Embed proportionate governance checkpoints into the DNA product lifecycle and confirm that material products have accountable owners approved sources and definitions quality controls usage guidance and certification evidence.

• Work with product and engineering teams from intake through release and ongoing operation so governance requirements are designed in rather than added late. Apply risk-based review criteria document conditions or exceptions and ensure certification can be revisited when sources transformations controls intended use or regulatory obligations materially change.
  

4. Stakeholder leadership risk assurance and change

• Lead governance forums and cross-functional engagement to resolve ownership definitions quality remediation product-readiness risk and exception decisions with clear actions and escalation paths.

• Prepare concise decision papers and governance reporting for senior stakeholders presenting the business impact control implications options dependencies and recommended action. Track commitments to closure and intervene when cross-domain conflicts delivery constraints or unresolved ownership place trusted outcomes at risk.

• Support data-risk assessments control reviews audits regulatory enquiries and remediation by maintaining clear evidence issue ownership exceptions and management reporting.

• Build governance capability through practical guidance training coaching and targeted automation of workflows metadata capture quality monitoring evidence and reporting.

• Promote adoption by integrating governance into existing delivery routines product ceremonies and operational processes. Identify opportunities to simplify controls reduce manual evidence gathering and improve user experience while maintaining appropriate accountability transparency and assurance.

Key deliverables

• Core deliverables include the governance roadmap and operating model; ownership and stewardship records; approved definitions metadata Critical Data Elements and quality rules; lineage and control evidence; product-certification records; issue and remediation reporting; and stewardship enablement materials.

Experience and qualifications

Essential:

• Bachelors degree or equivalent experience in Data Management Information Management Computer Science Information Systems Business Risk or a related discipline.

• At least eight years of relevant experience in data governance enterprise data management data quality metadata information architecture data risk or a related field.

• Demonstrable experience establishing or operationalising a data governance framework in a complex matrixed organisation.

• Strong working knowledge of data ownership and stewardship metadata and business semantics Critical Data Elements data quality lineage lifecycle controls and governance of data and analytics products.

• Experience facilitating governance councils working groups workshops and cross-functional decision forums.

• Ability to translate policies and technical concepts into practical business processes.

• Strong stakeholder-management and influencing skills including the ability to challenge constructively and obtain decisions from senior stakeholders.

• Practical understanding of data platforms data warehouses or lakes ETL or data pipelines BI environments and system integrations.

Desirable:

• Experience in banking financial services corporate real estate workplace services facilities asset management or another regulated environment.

• Familiarity with DAMA-DMBOK DCAM EDM Council practices or comparable data-management frameworks.

• Experience with enterprise data-governance catalogue metadata data-quality or lineage platforms.

• Working knowledge of SQL and the ability to interpret data models profiling outputs lineage and transformation logic.

• Familiarity with modern analytics business-intelligence distributed-data or cloud data platforms.

Leadership profile and success measures

The successful candidate is pragmatic outcome focused influential and technically credible. They create clarity across complex ownership and data flows challenge weak accountability constructively and build adoption through collaboration coaching and visible business value.

Success will be measured through ownership coverage for priority domains; completeness of approved definitions metadata lineage and quality controls; adoption of governance checkpoints; timely source remediation of material issues; product-certification status; closure of risk and audit actions; and stakeholder confidence in DNA-supported products.

The lead will establish a practical baseline and targets for these measures provide transparent reporting on progress and material exceptions and use the evidence to prioritise improvement. Success is demonstrated not only by completed governance artefacts but by faster decisions clearer accountability reduced recurrence of material data issues stronger audit readiness and increased reuse of trusted data products.

Why join Cushman & Wakefield

As one of the leading global real estate services firms transforming the way people work shop and live working at Cushman & Wakefield means you will benefit from;

• Being part of a growing global company;
• Career development and a promote from within culture;
• An organisation committed to Diversity and Inclusion

Were committed to providing work-life balance for our people in an inclusive rewarding environment.

We achieve this by providing a flexible and agile work environment by focusing on technology and autonomy to help our people achieve their career ambitions. We focus on career progression and foster a promotion from within culture leveraging global opportunities to ensure we retain our top talent. We encourage continuous learning and development opportunities to develop personal professional and technical capabilities and we reward with a comprehensive employee benefits program.

We have a vision of the future where people simply belong.

Thats why we support and celebrate inclusive causes not just on days of recognition throughout the year but every day. We embrace diversity across race colour religion sex national origin sexual orientation gender identity or persons with disabilities or protected veteran status. We ensure DEI is part of our DNA as a global community - it means we go way beyond than just talking about it - we live it. If you want to live it too join us.

INCO: Cushman & Wakefield