Data Governance Manager in Bury St Edmunds

Established in 1981 with a single store in the Northwest of England, the JD Group is a leading omni-channel retailer of Sports Fashion, Outdoors and Gyms with our colleagues working in stores across several retail fascias in many markets around the world. JD Sports Fashion Plc was listed on the London Stock Exchange in 1996 and has been a FTSE100 publicly quoted company since 2019 and continues to grow in the UK and internationally. We want to be the leading global omnichannel retailer in the sports and outdoor industry.

Data Governance Manager Role Overview

We are seeking a delivery-focused and pragmatic Data Governance Manager to establish, embed and scale data governance across the JD Group. This is a newly created role, reporting into the Head of Data Architecture, and will play a critical role in building the trusted, well-governed data foundations required to support analytics, regulatory compliance, and the responsible, ethical use of data within AI-driven innovation. You will be responsible for translating enterprise-level data architecture and governance strategy into practical, adopted governance operating models, starting with the Finance data domain and progressively expanding across the wider business.

Responsibilities

• Data Governance Strategy & Frameworks
  • 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.
• Ownership, Stewardship & Operating Model
  • 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) for technical governance within the data platform 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 ensure governance is embedded into data platform design, data pipelines and 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.
• Data Quality, Trust & Retention
  • 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.
• AI Data Governance & Ethics
  • 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.
• Stakeholder Engagement & Change
  • Act as the primary point of contact for data governance across JD.
  • Build strong relationships with Technology, Finance and wider business teams to drive engagement and adoption.
  • Clearly communicate the value of data governance to both technical and non-technical audiences.
  • Drive cultural change so that governance becomes part of “how we work” rather than a separate activity.
• Leadership & Capability Development
  • Operate initially as a senior individual contributor, delivering tangible outcomes hands-on.
  • Define the future shape of the Data Governance capability and support the Head of Data Architecture in scaling the function.
  • Contribute to the recruitment, onboarding and development of future data governance roles.
  • Promote a strong data culture, ownership mindset and continuous improvement ethos.

Role Objectives & KPIs

• Clear, adopted data ownership and stewardship within Finance.
• High-value data assets catalogued, discoverable and trusted via Dataplex and Alation.
• Improved transparency of data lineage and data quality across priority datasets.
• A scalable governance operating model ready to be rolled out across additional domains.
• Data governance embedded into architecture, platform and delivery processes.
• Clear governance, ownership and quality standards established for priority datasets.
• Strong transparency and auditability of data assets, enabling compliance and responsible AI use.
• Governance viewed as an enabler of better decisions and faster delivery.

Skills and Experience

• Significant senior-level experience implementing data governance in complex, evolving organisations including experience of introducing this and building governance from the ground up.
• At least five years’ experience driving the adoption of data governance principles within large, multifaceted organisations.
• Strong practical understanding of data governance concepts including ownership, stewardship, metadata, lineage and data quality.
• Hands-on experience with modern data governance or cataloguing tools (e.g. Alation, Dataplex, Collibra, Informatica or similar).
• Experience supporting data governance for advanced analytics or AI use cases, including understanding of data ethics, bias, transparency and explainability considerations.
• Experience working with cloud-based data platforms, ideally GCP.
• Ability to operate effectively across strategy, delivery and change.
• Strong stakeholder management and influencing skills, including working without formal authority.
• Effective communicator who can influence and engage senior stakeholders across business and technology domains who can provide authoritative guidance.
• Ability to simplify and demystify data governance, metadata, lineage and retention concepts to drive understanding and adoption across the business.

We know our colleagues work tirelessly to make JD Sports the success it is today and in turn, we offer them some amazing benefits including staff discount on JD Group and other brands within the organisation and personal development opportunities to learn and develop at work.