Head of IT - Data Governance

About the Role
The Head of IT Data Governance reports to the Group Head of IT and Security and is accountable for the quality, consistency, and usability of the data the IT function relies on to run and improve itself. This role involves leading the IT Data Programme and establishing and sustaining an IT data governance capability that keeps the data model accurate. This position is a governance role, not a data ownership role. The IT leader accountable for a service remains responsible for the data supporting that service. This role is responsible for implementing and operationalizing data governance across IT, in accordance with the Enterprise Data Governance framework, policies, and standards. Close collaboration with the Enterprise Data lead ensures alignment with enterprise governance, data quality, metadata, and information management requirements.

Key Responsibilities
Lead the IT Data Programme

• Own delivery of the IT Data Programme end-to-end, including the traceability model, the roadmap, and the implementation backlog.
• Ensure the programme addresses the business questions IT needs answered, avoiding becoming merely a documentation exercise. Every data requirement should trace back to a question, and every gap to a prioritized action.
• Transform assessment findings into a sequenced backlog with named owners and oversee until completion.

Implement and Operate the Data Governance Framework

• Operationalize the enterprise Data Governance Framework within IT and support the nomination of named Data Owners, Stewards, and Custodians across relevant IT data domains.
• Apply enterprise data governance decision rights, escalation pathways, and dispute resolution processes to IT data domains, escalating cross-functional matters through established enterprise governance arrangements.
• Establish and chair an IT Data Governance forum for decision-making, aligned with the Enterprise Data Governance Framework.
• Identify a network of data stewards in each IT function and assist in their training, standards, and processes.
• Hold Data Owners accountable for the quality of their domains and report non-compliance through appropriate escalations.

Maintain IT Data Standards, Definitions, and Authoritative Sources

• Develop and maintain IT domain-specific data definitions, metadata, reference data, and lifecycle requirements in accordance with enterprise data standards.
• Maintain the catalogue of IT systems of record and authoritative data sources while aligning with the enterprise data catalogue and metadata standards.
• Ensure IT data assets, ownership, classifications, definitions, and lineage are maintained in the enterprise data catalogue, collaborating with the Enterprise Data team.
• Govern alignment to the ServiceNow Common Service Data Model to ensure conformity with the enterprise IT data model.
• Enforce existing data standards that system integrations and tooling must meet before approval.

Data Quality, Measurement, and Remediation

• Implement the enterprise data quality framework across IT data domains, developing specific rules, thresholds, controls, and KPIs.
• Establish ongoing data quality measurement and remediation processes in alignment with enterprise data quality standards.
• Drive remediation of quality failures through accountable Data Owners, escalating any delays.
• Operate the IT data certification process for user trust in data.
• Manage the information lifecycle for IT data, ensuring compliance with Information Security policy.
• Promote data literacy across IT leadership, enhancing understanding of accountability among Data Owners.
• Publish and track an IT data maturity assessment with target states and measurable trajectories.

Reporting and Insight

• Lead development of trusted IT management reporting and performance measures, ensuring alignment with enterprise data architecture and standards.
• Ensure all metrics reported to leadership have defined calculations, named owners, and confidence levels.
• Reduce reporting duplication across the function and retire competing metric versions.
• Provide data foundations that quantify IT's impact on business productivity in hours and costs.

Enable AI and Automation

• Lead data readiness activities supporting enterprise AI and automation initiatives, ensuring alignment with data availability, quality, and governance requirements.
• Maintain classification and sensitivity positions for IT data sources feeding AI and automation tooling.
• Identify and prioritize data gaps preventing automation and self-healing capabilities.
• Collaborate with the Enterprise Data team to prioritize IT data improvements that support AI analytics and automation use cases.

Key Performance Indicators

• IT Data Programme milestones delivered on time.
• Percentage of in-scope IT data domains with a named Data Owner and Steward.
• Percentage of core IT data entities with defined authoritative sources.
• Data quality scores by domain compared to published thresholds.
• Number of remediated data quality defects trending downward.
• Completeness and accuracy of CMDB against the aligned target model.
• Percentage of leadership metrics with defined calculations, named owners, and stated confidence levels.
• Reduction in reports of competing measures.
• IT data maturity assessment score trending toward target.
• Number of business questions answered reliably.

Candidate Specification
Essential

• Extensive experience in leading data governance in complex organizations with evidence of results.
• Proven success in implementing Data Owner, Steward, and Custodian models while holding stakeholders accountable.
• Experience within Enterprise IT teams and knowledge of their structure and services.
• Strong technology domain knowledge, particularly in IT data areas such as configuration items, asset lifecycle, and risk management.
• Practical knowledge of ServiceNow CMDB and the Common Service Data Model.
• Experience establishing data quality frameworks, including measurement and reporting.
• Proven program leadership with accountability for advisory partners and deliverables.
• A track record of transforming assessments or strategies into actionable backlogs.
• Strong credibility and ability to challenge senior peers constructively.
• Ability to communicate the business consequences of data governance effectively.

Desirable

• Experience in professional services, engineering, or global matrix organizations.
• Background in data governance supporting enterprise AI initiatives.
• Experience with identity data governance, including service identities.
• Familiarity with enterprise architecture repositories or IT asset management tools.
• Formal data management qualifications alongside practical experience.
• Experience in building data steward networks.
• Capability in preparing governance papers for executive committees.

Personal Attributes

• Ability to exercise authority without direct control, influencing through governance and evidence.
• Pragmatic approach that values quick results over perfection.
• Persistent nature, understanding that data governance is a repeated effort.
• Direct communication style while maintaining relationships.
• Commercially aware, able to justify data investments effectively.
• Clear communicator who can make data governance engaging for diverse audiences.
• Focus on building capability in others.

Your Benefits and Rewards
Benefits vary by country and are subject to eligibility and local policy:

• Employee ownership model resulting in shared success through bonuses and career growth opportunities.
• Medical and life insurance as per local policies.
• Competitive annual leave aligned with local policies.
• Enhanced maternity and paternity leave provisions when applicable.
• Support for professional membership and subscriptions.
• Opportunities for learning and career development through diverse projects and structured training.
• A commitment to an inclusive culture that values diversity and equality.