Reporting, Analytics and AI Technical Lead

Reporting, Analytics and AI Lead

Job Summary

The Reporting, Analytics and AI Lead owns the design and delivery of analytics, data modelling, reporting, and AI-enabled consumption use cases through the enterprise data platform. This pivotal role is responsible for designing and delivering scalable, secure, and future-ready data modelling, reporting, and analytics through Azure, Fabric, and Purview, serving as the single source of truth for the enterprise. The role empowers business users to consume trusted, governed, and explainable data products through reporting, semantic models, and approved AI-enabled analytics tools. This is a technical delivery role focused on quality data, AI and analytics through the data platform—not a traditional BI role or general enterprise AI function.

Key Accountabilities

• Lead the design and delivery of trusted data, technical specifications, and data models across Azure, Fabric, and Purview to provide integrated, secure, and scalable data for consumption
• Own and deliver analytics, reporting, and AI-enabled consumption requirements.
• Own, design and deliver modelling, reporting and analytics products through the enterprise data platform
• Define, document, and validate reporting requirements, KPI definitions, business rules, management information logic, and analytics use cases. Define prioritisation, standards, delivery approach, and adoption metrics
• Partner with stakeholders to shape use cases, success measures, and iterative delivery plans.
• Deliver reporting, AI and analytics outputs that are trusted, governed, consistent, and suitable for senior stakeholder consumption
• Lead AI tools to answer business questions using approved, certified, and traceable data products. Validate AI for accuracy, context, source, assumptions, business meaning, and appropriate use
• Deliver and integrate AI-enabled analytics and data science capabilities. 
• Identify opportunities to and implement outputs that reduce manual reporting and replace with governed data products, semantic models, and AI-enabled analytics consumption
• Manage stakeholder expectations, prioritisation, adoption, feedback, and reporting rationalisation
• Support the transition from dashboard-led reporting to governed data products, semantic models, and AI-enabled consumption through the data platform
• Ensure AI-enabled analytics outputs are explainable, traceable, and aligned to approved metric definitions. Work with platform, governance, engineering, and modelling colleagues to ensure AI-enabled consumption is safe, controlled, and operationally supportable

Core Skills

• Expertise in semantic data modelling, including physical, dimensional, and logical models with deep understanding of BI patterns and enterprise architecture
• Highly skilled in building consistent metrics and reporting layers across governed platforms
• Advanced technical skills in hands-on delivery using Microsoft Azure, Fabric, and modern tools to deliver quality data through a data lakehouse
• Strong data visualisation and UX delivery; ability to critique and uplift data and reporting quality. Strong reporting, analytics, and management information capability
• Strong AI-enabled analytics, natural language querying, semantic consumption, and delivery of explainable analytical outputs. Ability to define and deliver safe and appropriate AI-enabled analytics use cases for the data platform
• Ability to validate AI-generated analytical answers for accuracy, context, assumptions, source data, and business meaning
• Working knowledge and skills in data science, AI, and machine learning applications in analytics and reporting, including responsible use controls
• Ability to work with engineers and modellers to translate business requirements into governed data products and semantic models; proven ability to deliver KPIs, measures, dimensions, and reusable business logic
• Skills in semantic models, certified datasets, controlled self-service analytics, and AI-enabled consumption patterns
• Understanding of data sensitivity, access controls, governance requirements, and responsible use of AI-generated outputs. Ability to support adoption of AI-enabled analytics while managing risks, user expectations, and appropriate use
• Leadership, coaching, stakeholder and mentoring skills
• Passion for data and innovation to implement global best practice in modern, scalable, and future-proof reporting and analytics

Required Experience

• Bachelor's degree in data analytics, data science, or related field
• Extensive experience in data, AI and analytics delivery with a proven track record of delivering secure, high-value data, AI and analytics products and measurable business impact. Proven experience in semantic data model delivery.
• Experience in leadership and line management; must have worked in a technical data team, mentored and led other team members, and worked with a Chief Data Officer
• Extensive experience implementing Microsoft Azure and self-service data platform frameworks at scale through the consumption layer. Experience in data standardisation frameworks for harmonising data definitions, taxonomies, and formats across regions
• Experience translating business requirements into data products, semantic models, reports, or analytical outputs
• Experience rationalising reports, metrics, dashboards, management information processes and self-service analytics environments
• Experience supporting senior stakeholders with trusted reporting and analytics; track record of delivering executive-certified data, AI and analytics products with high adoption. Experience validating outputs for senior management or executive reporting
• Experience delivering data science, advanced analytics, and AI-assisted analytics capabilities integrated with governed data platforms
• Experience working closely with data engineers, architects, and business domain leads to design and deliver technical specifications and model design

• Experience supporting AI-enabled analytics, natural language querying, automated insights, semantic search, or AI consumption layers
• Awareness of relevant AI governance frameworks such as NIST AI Risk Management, ISO AI Management standards, Responsible AI principles, or equivalent enterprise control frameworks
• Relevant analytics, data, Power BI, SQL, Microsoft reporting, Azure, AI analytics, or data platform certifications

At RES we celebrate difference as we know it makes our company a great place to work. Encouraging applicants with different backgrounds, ideas and points of view, we create teams who work together to solve complex problems and design practical solutions for our clients. Our multiple perspectives come from many sources including the diverse ethnicity, culture, gender, nationality, age, sex, sexual orientation, gender identity and expression, disability, marital status, parental status, education, social background and life experience of our people.

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