Data Strategy & Engineering Lead

• Define and own the Digital & IT data strategy in partnership with Product leadership, ensuring alignment with product, technology (IT and Networks), and commercial objectives.
• Establish data, analytics, and AI as core enablers of business growth, customer experience excellence, and operational effectiveness.
• Define and maintain a clear, prioritised roadmap covering data platforms, analytics, and AI capabilities.
• Own the end-to-end enterprise data architecture across digital channels, BSS/IT systems, and network domains, in close collaboration with architecture teams.
• Ensure seamless data integration across customer journeys, IT platforms, and network telemetry to enable insight, automation, and predictive capabilities at scale.
• Set and govern enterprise standards for data platforms, pipelines, analytics engineering, and AI solutions.
• Lead the delivery of advanced analytics and AI capabilities from ideation through to production deployment.
• Ensure all data products, models, and insights are production-grade, governed, monitored, and measured for business value.
• Drive high-value data and AI use cases across customer experience, product performance, monetisation, network optimisation, and operational efficiency.
• Ensure data capabilities support the needs of global customers operating across multiple markets and regulatory environments.
• Apply data sovereignty principles, including data residency, access controls, and processing constraints by design.
• Ensure compliance with GDPR and applicable regional data regulations across products, platforms, and services.
• Act as a senior data representative with customers, partners, regulators, and auditors where required.
• Hold end-to-end accountability for the organisation's data governance framework, including policies, standards, controls, and decision forums.
• Embed data governance as a living operational practice across Digital & IT and wider business functions.
• Define and enforce clear data ownership, stewardship, and accountability models.
• Ensure consistent application of data quality, lineage, access control, ethics, and lifecycle management standards.
• Define the operating model for Data Science and Data Engineering, including internal teams, strategic partners, and vendors.
• Influence and align cross-functional teams across Product, Technology, Networks, Operations, and Commercial functions.
• Build and sustain a culture of accountability, innovation, quality, and continuous improvement.

• Senior leadership experience (5+ years) across Data Architecture, Data Science, Analytics, and Data Engineering within large-scale enterprise environments.
• Deep industry experience (15+ years) spanning Analytics, Digital & IT, Cloud Technologies, and Network/Infrastructure data domains, with a strong understanding of how these areas interconnect.
• Proven delivery of end-to-end data capabilities, covering customer, commercial, IT, and network-related domains from strategy through execution.
• Experience designing and scaling modern cloud-based data platforms, including technologies such as GCP, BigQuery, Dataflow, Dataproc, Azure, AWS, or equivalent solutions.
• Strong understanding of modern data architectures, including data lakes, lakehouse architectures, streaming platforms, real-time processing, and event-driven ecosystems.
• Experience establishing data as a strategic product, enabling business growth, customer value, operational performance, and commercial outcomes.
• Strong track record in defining and embedding enterprise data governance, successfully operating across multiple functions and organisational boundaries.
• Expert knowledge of data sovereignty, GDPR, privacy, and regulatory frameworks, with the ability to translate requirements into practical operating models.
• Experience leading high-performing Data Science, Analytics, and Data Engineering teams, delivering measurable business impact.
• Knowledge of AI, Machine Learning, and Advanced Analytics delivery, including governance, operationalisation, and value measurement.
• Strong stakeholder management and executive communication skills, with the ability to influence senior leaders, customers, and external partners.
• Experience operating within complex global organisations, managing multiple stakeholders, priorities, and regulatory requirement

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