Senior Manager, Group Finance - Systems & Analytics

The candidate will be part of the Group Finance - Systems & Analytics team and play a key role in building the Group's finance data, analytics and AI capabilities. 

The role will be instrumental in designing, developing and implementing the Group's Enterprise Finance Data Lake and AI platform, establishing enterprise finance data models, semantic layers and governance frameworks, and enabling AI-powered solutions that enhance reporting, analytics, decision support and process automation across the Group. 

This is a hands-on role requiring a combination of data engineering, analytics, AI solution development and business partnering skills. The successful candidate will work closely with Finance, IT, business stakeholders and technology partners to deliver scalable data and AI solutions while building the internal capabilities required for Group Finance to progressively maintain, enhance and expand its own AI solutions over time. 

Finance Data Platform & Governance 

• Design, develop and manage the Group Finance data platform, including curated finance datasets, semantic models and enterprise data structures supporting reporting, analytics and AI initiatives. 
• Build and maintain scalable data integration and transformation pipelines across finance and operational systems. 
• Establish and enforce data governance, metadata management, master data and data quality standards to ensure trusted and consistent finance information. 
• Partner with IT and technology teams to develop a secure, scalable and future-ready finance data architecture. 

Data Modelling & Semantic Layer 

• Design and maintain enterprise finance data models, semantic layers and finance ontology to support reporting, planning, performance management and AI-driven use cases. 
• Standardise KPI definitions, business logic and metric calculations to establish a single source of truth across the Group. 
• Translate business requirements into scalable data products and analytics solutions that improve data accessibility, consistency and transparency. 
• Support self-service analytics and reporting capabilities through business-friendly data models and semantic structures. 

Analytics, Reporting & Business Insights 

• Develop and enhance reporting, dashboard and analytics solutions to support financial, management and operational decision-making. 
• Standardise KPI definitions, reporting logic and business metrics across the Group. 
• Enable self-service analytics and improve data accessibility, transparency and consistency for finance stakeholders. 
• Drive automation and continuous improvement initiatives to enhance reporting efficiency and reduce manual effort. 

AI Solutions & Intelligent Automation 

• Design and implement data and knowledge foundations required for AI-powered finance solutions. 
• Develop, deploy and continuously enhance AI-enabled solutions, intelligent automation and generative AI use cases that improve productivity and decision support. 
• Collaborate with stakeholders to identify, prioritise and deliver high-impact AI initiatives across Finance. 
• Establish AI governance, MLOps practices, reusable assets, development standards, including model deployment, monitoring and continuous improvement to ensure AI solutions remain scalable, reliable and sustainable. 
• Support use cases including reporting automation, financial analysis, forecasting, knowledge search, document processing and performance insights. 

Stakeholder Management & Transformation 

• Partner with Finance, IT and business stakeholders to define and deliver data, analytics and AI solutions aligned with business priorities. 
• Manage solution delivery across design, development, testing and implementation phases. 
• Work closely with technology vendors and implementation partners where required. 
• Promote adoption of modern data, analytics and AI capabilities across the Finance function. 
• Stay abreast of emerging technologies and recommend innovative solutions to enhance finance capabilities.

QUALIFICATIONS & EXPERIENCE 

Required 

• Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Accountancy, Finance or a related discipline.
• Minimum 7 years of relevant experience in data engineering, data architecture, analytics, business intelligence, finance systems or AI solution development.
• Proven experience designing and implementing enterprise data platforms, cloud-based analytics solutions or modern data architectures.
• Strong hands-on experience in SQL, Python, data modelling and data integration.
• Experience building scalable data pipelines and managing large, complex datasets across multiple systems.
• Experience delivering analytics, automation or AI solutions in a business environment.
• Strong stakeholder management, communication and problem-solving skills.
• Ability to translate business requirements into practical and scalable technology solutions. 

Preferred 

• Experience with modern cloud data platforms and analytics technologies such as Google Cloud Platform (GCP), BigQuery, Databricks, Microsoft Fabric, Azure Data Lake or equivalent.
• Experience with AI, Generative AI, AI agents, automation frameworks and modern analytics solutions.
• Finance domain knowledge, particularly in financial reporting, FP&A, consolidation, enterprise performance management or management reporting.
• Experience supporting finance transformation, ERP or enterprise system implementation programmes.
• Familiarity with finance platforms such as SAP S/4HANA, Oracle, Workday, OneStream, IBM Planning Analytics or Hyperion.
• Experience in data governance, master data management, semantic modelling, knowledge repositories or enterprise data frameworks.
• Demonstrated ability to bridge business requirements and technology delivery in a complex enterprise environment.