Director Of Supply Chain Data Solutions- London

Director of Supply Chain Data Solutions – London

Reporting to the CTO.

Qualifications

• Bachelor’s degree in Data Science, Supply Chain Management, Business Administration, or a related field; advanced degree preferred.
• 10+ years of experience in data analytics, data governance, or enterprise data management, with a focus on supply chain operations.
• Proven experience in delivering dashboards, analytics tools, and data solutions that drive business outcomes.
• Strong knowledge of data governance frameworks, standards, and best practices.
• Expertise in enterprise data management, including data modeling, integration, and synchronization across systems.
• Familiarity with digital transformation initiatives within supply chain and related functions.
• Proficiency in data visualization tools (e.g., Tableau, Power BI), analytics platforms, and database management systems.
• Exceptional leadership and communication skills, with the ability to collaborate across diverse teams and influence stakeholders at all levels.
• Strong problem‑solving and critical‑thinking abilities, with a focus on driving continuous improvement.
• Experience with advanced analytics, machine learning, or AI‑driven solutions in supply chain operations.
• Knowledge of ERP systems (e.g., SAP, Oracle) and their integration with data platforms.
• Certification in data governance or data management frameworks (e.g., DAMA, CDMP).
• Experience in managing large‑scale digital transformation projects.
• Strong collaboration with team members and other departments.
• Detail orientated with analytical, time management and problem‑solving skills.
• Excellent written and verbal communication skills.

Responsibilities

Data Architecture

• Develop and maintain a robust and scalable data architecture that supports the end‑to‑end supply chain process.
• Collaborate with cross‑functional teams to define data integration points and ensure data flows seamlessly across systems.
• In collaboration with IT, oversee the design and implementation of data models, data warehouses, and data pipelines to support data analytics and reporting.
• Collaborate with business stakeholders to translate their needs into scalable and efficient data solutions that support digital transformation initiatives.
• Design and implement robust data architectures that enable seamless integration across systems and applications while ensuring scalability and efficiency.
• Partner with IT and project teams to deliver data solutions aligned with transformation outcomes, including automation, advanced analytics, and AI‑driven insights.
• Act as a strategic advisor for digital projects, ensuring data requirements are met while driving innovation and efficiency.

Data Governance

• Establish and enforce data governance standards, policies, and procedures to ensure data quality, consistency, and accuracy across the organization.
• Lead efforts to improve master data quality and manage data hierarchies, taxonomies, and definitions for key supply chain data elements.
• Facilitate cross‑functional alignment and collaboration to ensure data is structured, organized, accessible, and leveraged effectively.
• Monitor and maintain compliance with regulatory requirements and industry standards related to data management.

Enterprise Data Management

• Ensure the integrity, consistency, and accessibility of critical data across Supply Chain, Sales Enablement, and Finance/Accounting organizations.
• Develop and maintain enterprise‑wide data models, ensuring alignment with organizational goals and objectives.
• Implement processes and tools to streamline data integration and synchronization across systems and departments.
• Lead efforts to identify and resolve data discrepancies, ensuring a single source of truth for enterprise data.

AI Strategy and Roadmap

• In partnership with the Senior Director Digital transformation, develop and communicate a comprehensive AI strategy aligned with the company’s supply chain objectives and long‑term business goals.
• Identify AI opportunities and use cases that can enhance supply chain efficiency.
• Drive the deployment of AI‑powered tools to support decision‑making, process automation, and data‑driven insights.
• Create a roadmap for the successful implementation of AI solutions, considering scalability, feasibility, and ROI.
• Stay abreast of the latest advancements in AI and machine learning technologies, and assess their potential impact on supply chain operations.

Team Leadership

• Provide strategic direction and mentorship to the data services team, fostering a culture of collaboration, continuous learning, and excellence.
• Identify talent gaps and implement strategies to attract, retain, and develop top talent.
• Set clear performance goals, conduct regular performance evaluations, and identify opportunities for professional development.

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