Data Governance Manager

Data Governance Manager

We are seeking a delivery‑focused and pragmatic Data Governance Manager to establish, embed and scale data governance across the JD Group. This newly created role reports to the Head of Data Architecture and will play a critical role in building trusted, well‑governed data foundations required to support analytics, regulatory compliance, and responsible use of data within AI‑driven innovation.

You will be responsible for translating enterprise‑level data architecture and governance strategy into practical and adopted governance operating models, starting with the Finance data domain and progressively expanding across the wider business. The role is strategic yet hands‑on, with responsibility for designing frameworks, configuring tooling, and driving adoption directly.

The role will play a key part in ensuring that data used to train, power and operate AI products is high quality, transparent, well‑controlled and ethically sourced, aligned to JD’s AI governance principles.

• Own the design and implementation of JD’s data governance approach in alignment with the Group Data Architecture vision and standards.
• Define pragmatic governance frameworks covering data ownership and stewardship, critical data elements and data classification, metadata, lineage and transparency, and data quality management and controls.
• Ensure governance frameworks are scalable, repeatable and proportionate, enabling delivery rather than slowing it down.
• Contribute to the evolution of group‑wide data architecture and governance standards and playbooks.
• Establish and embed a clear data ownership and stewardship model, initially within the Finance domain.
• Work closely with Finance stakeholders to formalise roles, responsibilities and accountability for data.
• Create operating models, playbooks and guidance that can be reused across additional data domains.
• Act as a trusted advisor and coach to data owners and stewards, supporting capability uplift across the business.
• Lead the implementation and adoption of data governance tooling, including Dataplex (GCP) and Alation as the enterprise data catalogue and lineage solution.
• Define and enforce standards for metadata, lineage and certification of trusted data assets.
• Partner with Data Architecture and Data Engineering teams to embed governance into data platform design, data pipelines, models and analytics and reporting assets.
• Ensure AI‑relevant datasets, features and derived data products are fully catalogued, classified and traceable within governance tooling to support transparency and explainability.
• Define JD’s approach to data quality management and data retention, aligned to architectural standards and business priorities.
• Work with business and technical teams to identify critical data assets and agree quality expectations.
• Establish and embed JD’s data retention policy, agreeing a prioritised roadmap with technical stakeholders for implementation.
• Enable transparency of data quality metrics and lineage to build confidence in analytics, reporting and AI use cases and support remediation of data quality issues through clear ownership and prioritisation.
• Define heightened data quality, completeness and monitoring expectations for datasets used in AI and automated decision‑making use cases.
• Ensure that data used to train, power and operate AI and advanced analytics use cases is well‑governed, high quality, transparent and ethically used.
• Partner with Data Science, AI and Product teams to embed data ownership, lineage, quality and bias considerations into AI design and delivery.
• Provide data governance input into AI approval and assurance processes, ensuring AI use cases are supported by trusted and well‑controlled data.
• Support the Head of Data Architecture in embedding enterprise‑grade governance, security and compliance across the data estate.
• Ensure governance practices align with data security, privacy, regulatory and ethical requirements, including where data is used in AI and automated decision‑making.
• Contribute to architectural reviews and design governance where data standards and controls are required.
• Act as the primary point of…