Data and AI Governance Lead The Data and AI Governance Lead owns the governance framework for enterprise data and AI-enabled analytics across Azure, Fabric, and Purview. The role ensures data is classified, trusted, controlled, auditable, and safe for consumption by reporting, analytics, and AI tools - and that the platform is secure with continuously improving data quality. The postholder works with business data owners, IT security, architecture, engineering, and analytics teams to embed governance into ways of working, tooling, and technical delivery. Key Accountabilities Own and mature the data and AI governance framework across Fabric, Purview, and the AI-enabled analytics platform; author and maintain policies and standards for data quality, metadata, lineage, retention, privacy, and ethical data and AI usage. Implement and own Purview catalogue, classification, lineage, glossary, data ownership, and certified dataset processes; drive master and reference data alignment of definitions, KPIs, and semantic standards across domains. Define and operate governance controls for AI-enabled data consumption, including the AI use case register covering risk rating, approval status, required controls, and review dates; establish the control checklist required before any AI use case goes live. Define rules for what data AI tools can and cannot access; ensure AI tools only consume approved, certified, classified, and traceable data with appropriate controls for prompt handling, output handling, personal data, sensitive data, and commercially sensitive data. Own audit evidence for AI-enabled data products including data source classification, ownership, access model, metric definition, lineage, and approval history. Implement data quality management including critical data elements, rule sets, monitoring, issue management, and remediation workflows; establish data quality standards, stewardship, and data owner accountability. Partner with cyber, legal, privacy, P&C, and business data owners to ensure AI use of enterprise data is safe, compliant, and auditable; partner with Cyber/InfoSec on data classification, access control, segregation of duties, and audit readiness. Support responsible AI practices including human oversight, explainability, traceability, and appropriate use of AI-generated outputs; support AI/ML governance including model risk controls, data suitability checks, and bias and ethical considerations. Skills and Competencies Strong hands on expertise in Microsoft Purview: metadata management, classification, glossary, lineage, and certified dataset governance. Strong understanding of AI governance, responsible AI, AI risk assessment, and AI control frameworks; ability to classify AI use cases by risk and define appropriate pre go live controls. Ability to translate AI governance principles into practical technical controls implementable by engineers and architects, including prompt governance, output governance, data access controls, and audit evidence. Strong understanding of personal, sensitive, employee, and commercially sensitive data and access restrictions. Data quality framework design, data ownership, stewardship, and issue management; experience with profiling, rule design, monitoring, and root cause analysis. Knowledge of GDPR and PII controls with practical implementation experience in Azure. Strong stakeholder management across data, cyber, legal, privacy, P&C, and business domains; ability to challenge unsafe AI use cases and translate between technical and business audiences. Experience embedding governance into delivery pipelines including CI/CD, data contracts, and automated checks. Qualifications and Experience Bachelor's degree in data analytics, data governance, data science, or a related discipline. Significant experience leading technical data governance in Microsoft Azure with a proven track record of improving data quality and stewardship using modern tooling. Extensive hands on experience with Microsoft Purview across an Azure data platform, with evidenced improvements to data quality and standardisation in a global context. Experience governing sensitive enterprise data including personal data, employee data, and business critical reporting data. Experience in AI governance, responsible AI, AI risk management, or AI data access controls; familiarity with frameworks such as NIST AI Risk Management, ISO AI Management standards, or equivalent. Practical implementation of international data standardisation frameworks for harmonising definitions, taxonomies, and formats across regions. Experience automating governance using modern tooling and embedding controls into data platform delivery. Relevant certifications such as DAMA/CDMP, DCAM, privacy, cloud, AI governance, or equivalent. Experience with AI/ML and data science platform use cases with comprehensive technical governance. Equal Opportunity Employer At RES we celebrate difference. We encourage applicants from diverse backgrounds, ideas, and points of view to build teams that solve complex problems. RES is an equal opportunity employer and we welcome candidates of all backgrounds.
15/07/2026
Full time
Data and AI Governance Lead The Data and AI Governance Lead owns the governance framework for enterprise data and AI-enabled analytics across Azure, Fabric, and Purview. The role ensures data is classified, trusted, controlled, auditable, and safe for consumption by reporting, analytics, and AI tools - and that the platform is secure with continuously improving data quality. The postholder works with business data owners, IT security, architecture, engineering, and analytics teams to embed governance into ways of working, tooling, and technical delivery. Key Accountabilities Own and mature the data and AI governance framework across Fabric, Purview, and the AI-enabled analytics platform; author and maintain policies and standards for data quality, metadata, lineage, retention, privacy, and ethical data and AI usage. Implement and own Purview catalogue, classification, lineage, glossary, data ownership, and certified dataset processes; drive master and reference data alignment of definitions, KPIs, and semantic standards across domains. Define and operate governance controls for AI-enabled data consumption, including the AI use case register covering risk rating, approval status, required controls, and review dates; establish the control checklist required before any AI use case goes live. Define rules for what data AI tools can and cannot access; ensure AI tools only consume approved, certified, classified, and traceable data with appropriate controls for prompt handling, output handling, personal data, sensitive data, and commercially sensitive data. Own audit evidence for AI-enabled data products including data source classification, ownership, access model, metric definition, lineage, and approval history. Implement data quality management including critical data elements, rule sets, monitoring, issue management, and remediation workflows; establish data quality standards, stewardship, and data owner accountability. Partner with cyber, legal, privacy, P&C, and business data owners to ensure AI use of enterprise data is safe, compliant, and auditable; partner with Cyber/InfoSec on data classification, access control, segregation of duties, and audit readiness. Support responsible AI practices including human oversight, explainability, traceability, and appropriate use of AI-generated outputs; support AI/ML governance including model risk controls, data suitability checks, and bias and ethical considerations. Skills and Competencies Strong hands on expertise in Microsoft Purview: metadata management, classification, glossary, lineage, and certified dataset governance. Strong understanding of AI governance, responsible AI, AI risk assessment, and AI control frameworks; ability to classify AI use cases by risk and define appropriate pre go live controls. Ability to translate AI governance principles into practical technical controls implementable by engineers and architects, including prompt governance, output governance, data access controls, and audit evidence. Strong understanding of personal, sensitive, employee, and commercially sensitive data and access restrictions. Data quality framework design, data ownership, stewardship, and issue management; experience with profiling, rule design, monitoring, and root cause analysis. Knowledge of GDPR and PII controls with practical implementation experience in Azure. Strong stakeholder management across data, cyber, legal, privacy, P&C, and business domains; ability to challenge unsafe AI use cases and translate between technical and business audiences. Experience embedding governance into delivery pipelines including CI/CD, data contracts, and automated checks. Qualifications and Experience Bachelor's degree in data analytics, data governance, data science, or a related discipline. Significant experience leading technical data governance in Microsoft Azure with a proven track record of improving data quality and stewardship using modern tooling. Extensive hands on experience with Microsoft Purview across an Azure data platform, with evidenced improvements to data quality and standardisation in a global context. Experience governing sensitive enterprise data including personal data, employee data, and business critical reporting data. Experience in AI governance, responsible AI, AI risk management, or AI data access controls; familiarity with frameworks such as NIST AI Risk Management, ISO AI Management standards, or equivalent. Practical implementation of international data standardisation frameworks for harmonising definitions, taxonomies, and formats across regions. Experience automating governance using modern tooling and embedding controls into data platform delivery. Relevant certifications such as DAMA/CDMP, DCAM, privacy, cloud, AI governance, or equivalent. Experience with AI/ML and data science platform use cases with comprehensive technical governance. Equal Opportunity Employer At RES we celebrate difference. We encourage applicants from diverse backgrounds, ideas, and points of view to build teams that solve complex problems. RES is an equal opportunity employer and we welcome candidates of all backgrounds.
RES is looking for a Data and AI Governance Lead to oversee the governance framework for enterprise data and AI analytics. This role will ensure data is secure, classified, and maintained at high standards. The ideal candidate will have significant experience in Microsoft Azure and a Bachelor's degree in a data-related field. Responsibilities include collaborating with IT teams, implementing data quality measures, and ensuring AI use is safe and compliant with regulations.
15/07/2026
Full time
RES is looking for a Data and AI Governance Lead to oversee the governance framework for enterprise data and AI analytics. This role will ensure data is secure, classified, and maintained at high standards. The ideal candidate will have significant experience in Microsoft Azure and a Bachelor's degree in a data-related field. Responsibilities include collaborating with IT teams, implementing data quality measures, and ensuring AI use is safe and compliant with regulations.
Data and AI Governance Lead The Data and AI Governance Lead owns the governance framework for enterprise data and AI-enabled analytics across Azure, Fabric, and Purview. The role ensures data is classified, trusted, controlled, auditable, and safe for consumption by reporting, analytics, and AI tools - and that the platform is secure with continuously improving data quality. The postholder works with business data owners, IT security, architecture, engineering, and analytics teams to embed governance into ways of working, tooling, and technical delivery. Key Accountabilities Own and mature the data and AI governance framework across Fabric, Purview, and the AI-enabled analytics platform; author and maintain policies and standards for data quality, metadata, lineage, retention, privacy, and ethical data and AI usage. Implement and own Purview catalogue, classification, lineage, glossary, data ownership, and certified dataset processes; drive master and reference data alignment of definitions, KPIs, and semantic standards across domains. Define and operate governance controls for AI-enabled data consumption, including the AI use case register covering risk rating, approval status, required controls, and review dates; establish the control checklist required before any AI use case goes live. Define rules for what data AI tools can and cannot access; ensure AI tools only consume approved, certified, classified, and traceable data with appropriate controls for prompt handling, output handling, personal data, sensitive data, and commercially sensitive data. Own audit evidence for AI-enabled data products including data source classification, ownership, access model, metric definition, lineage, and approval history. Implement data quality management including critical data elements, rule sets, monitoring, issue management, and remediation workflows; establish data quality standards, stewardship, and data owner accountability. Partner with cyber, legal, privacy, P&C, and business data owners to ensure AI use of enterprise data is safe, compliant, and auditable; partner with Cyber/InfoSec on data classification, access control, segregation of duties, and audit readiness. Support responsible AI practices including human oversight, explainability, traceability, and appropriate use of AI-generated outputs; support AI/ML governance including model risk controls, data suitability checks, and bias and ethical considerations. Skills and Competencies Strong hands on expertise in Microsoft Purview: metadata management, classification, glossary, lineage, and certified dataset governance. Strong understanding of AI governance, responsible AI, AI risk assessment, and AI control frameworks; ability to classify AI use cases by risk and define appropriate pre go live controls. Ability to translate AI governance principles into practical technical controls implementable by engineers and architects, including prompt governance, output governance, data access controls, and audit evidence. Strong understanding of personal, sensitive, employee, and commercially sensitive data and access restrictions. Data quality framework design, data ownership, stewardship, and issue management; experience with profiling, rule design, monitoring, and root cause analysis. Knowledge of GDPR and PII controls with practical implementation experience in Azure. Strong stakeholder management across data, cyber, legal, privacy, P&C, and business domains; ability to challenge unsafe AI use cases and translate between technical and business audiences. Experience embedding governance into delivery pipelines including CI/CD, data contracts, and automated checks. Qualifications and Experience Bachelor's degree in data analytics, data governance, data science, or a related discipline. Significant experience leading technical data governance in Microsoft Azure with a proven track record of improving data quality and stewardship using modern tooling. Extensive hands on experience with Microsoft Purview across an Azure data platform, with evidenced improvements to data quality and standardisation in a global context. Experience governing sensitive enterprise data including personal data, employee data, and business critical reporting data. Experience in AI governance, responsible AI, AI risk management, or AI data access controls; familiarity with frameworks such as NIST AI Risk Management, ISO AI Management standards, or equivalent. Practical implementation of international data standardisation frameworks for harmonising definitions, taxonomies, and formats across regions. Experience automating governance using modern tooling and embedding controls into data platform delivery. Relevant certifications such as DAMA/CDMP, DCAM, privacy, cloud, AI governance, or equivalent. Experience with AI/ML and data science platform use cases with comprehensive technical governance. Equal Opportunity Employer At RES we celebrate difference. We encourage applicants from diverse backgrounds, ideas, and points of view to build teams that solve complex problems. RES is an equal opportunity employer and we welcome candidates of all backgrounds.
15/07/2026
Full time
Data and AI Governance Lead The Data and AI Governance Lead owns the governance framework for enterprise data and AI-enabled analytics across Azure, Fabric, and Purview. The role ensures data is classified, trusted, controlled, auditable, and safe for consumption by reporting, analytics, and AI tools - and that the platform is secure with continuously improving data quality. The postholder works with business data owners, IT security, architecture, engineering, and analytics teams to embed governance into ways of working, tooling, and technical delivery. Key Accountabilities Own and mature the data and AI governance framework across Fabric, Purview, and the AI-enabled analytics platform; author and maintain policies and standards for data quality, metadata, lineage, retention, privacy, and ethical data and AI usage. Implement and own Purview catalogue, classification, lineage, glossary, data ownership, and certified dataset processes; drive master and reference data alignment of definitions, KPIs, and semantic standards across domains. Define and operate governance controls for AI-enabled data consumption, including the AI use case register covering risk rating, approval status, required controls, and review dates; establish the control checklist required before any AI use case goes live. Define rules for what data AI tools can and cannot access; ensure AI tools only consume approved, certified, classified, and traceable data with appropriate controls for prompt handling, output handling, personal data, sensitive data, and commercially sensitive data. Own audit evidence for AI-enabled data products including data source classification, ownership, access model, metric definition, lineage, and approval history. Implement data quality management including critical data elements, rule sets, monitoring, issue management, and remediation workflows; establish data quality standards, stewardship, and data owner accountability. Partner with cyber, legal, privacy, P&C, and business data owners to ensure AI use of enterprise data is safe, compliant, and auditable; partner with Cyber/InfoSec on data classification, access control, segregation of duties, and audit readiness. Support responsible AI practices including human oversight, explainability, traceability, and appropriate use of AI-generated outputs; support AI/ML governance including model risk controls, data suitability checks, and bias and ethical considerations. Skills and Competencies Strong hands on expertise in Microsoft Purview: metadata management, classification, glossary, lineage, and certified dataset governance. Strong understanding of AI governance, responsible AI, AI risk assessment, and AI control frameworks; ability to classify AI use cases by risk and define appropriate pre go live controls. Ability to translate AI governance principles into practical technical controls implementable by engineers and architects, including prompt governance, output governance, data access controls, and audit evidence. Strong understanding of personal, sensitive, employee, and commercially sensitive data and access restrictions. Data quality framework design, data ownership, stewardship, and issue management; experience with profiling, rule design, monitoring, and root cause analysis. Knowledge of GDPR and PII controls with practical implementation experience in Azure. Strong stakeholder management across data, cyber, legal, privacy, P&C, and business domains; ability to challenge unsafe AI use cases and translate between technical and business audiences. Experience embedding governance into delivery pipelines including CI/CD, data contracts, and automated checks. Qualifications and Experience Bachelor's degree in data analytics, data governance, data science, or a related discipline. Significant experience leading technical data governance in Microsoft Azure with a proven track record of improving data quality and stewardship using modern tooling. Extensive hands on experience with Microsoft Purview across an Azure data platform, with evidenced improvements to data quality and standardisation in a global context. Experience governing sensitive enterprise data including personal data, employee data, and business critical reporting data. Experience in AI governance, responsible AI, AI risk management, or AI data access controls; familiarity with frameworks such as NIST AI Risk Management, ISO AI Management standards, or equivalent. Practical implementation of international data standardisation frameworks for harmonising definitions, taxonomies, and formats across regions. Experience automating governance using modern tooling and embedding controls into data platform delivery. Relevant certifications such as DAMA/CDMP, DCAM, privacy, cloud, AI governance, or equivalent. Experience with AI/ML and data science platform use cases with comprehensive technical governance. Equal Opportunity Employer At RES we celebrate difference. We encourage applicants from diverse backgrounds, ideas, and points of view to build teams that solve complex problems. RES is an equal opportunity employer and we welcome candidates of all backgrounds.
RES is looking for a Data and AI Governance Lead to oversee the governance framework for enterprise data and AI analytics. This role will ensure data is secure, classified, and maintained at high standards. The ideal candidate will have significant experience in Microsoft Azure and a Bachelor's degree in a data-related field. Responsibilities include collaborating with IT teams, implementing data quality measures, and ensuring AI use is safe and compliant with regulations.
15/07/2026
Full time
RES is looking for a Data and AI Governance Lead to oversee the governance framework for enterprise data and AI analytics. This role will ensure data is secure, classified, and maintained at high standards. The ideal candidate will have significant experience in Microsoft Azure and a Bachelor's degree in a data-related field. Responsibilities include collaborating with IT teams, implementing data quality measures, and ensuring AI use is safe and compliant with regulations.
RES is seeking a Global Cyber Architect to support the Director of Cyber Security and the Group CIO in designing and operating cyber security for IT and OT systems. The role requires collaboration with cyber service providers, internal teams and key stakeholders to embed security into business practices. You will travel periodically to RES sites to build relationships and ensure effective delivery of cyber security services, aiming to position RES as a market leader in renewables security
12/07/2026
Full time
RES is seeking a Global Cyber Architect to support the Director of Cyber Security and the Group CIO in designing and operating cyber security for IT and OT systems. The role requires collaboration with cyber service providers, internal teams and key stakeholders to embed security into business practices. You will travel periodically to RES sites to build relationships and ensure effective delivery of cyber security services, aiming to position RES as a market leader in renewables security
Job Summary This is a rare opportunity to join a newly created global data modelling lead role, in a growing central data and analytics team. Your key work will be to lead the design and build of governed, reusable global data models that translate enterprise data into business ready dimensions, facts and metrics for consistent reporting, self service reporting, analytics and AI/ML readiness. You will be the bridge between the data team, IT leaders and business leaders: understanding and defining requirements, shaping data products, modelling business logic, and enabling performant, well documented accurate data delivery at a global scale. This work relates predominantly in year one to corporate services data, specifically finance and human resources. You will be the global lead in RES for data modelling and analytics engineering, educating and training regional staff, providing templates and guidance on best practice. Lead working groups with the business/IT and define comprehensive business requirements from stakeholders. From the business requirements assess buy versus build options and if a data platform build is chosen then design the data model in conjunction with IT/data teams and business domain leaders. Once signed off, build, deliver and maintain a comprehensive, scalable data model and lead implementation, optimisation, and scalability. Accountabilities Design global data models aligned to agreed business definitions, KPIs and reporting departments in conjunction with executives, business domains and senior IT leaders. Develop and maintain metric definitions and calculation logic to ensure model consistency across dashboards and reports. Build, deliver and maintain curated data modelling and products with documentation, tests, and versioning. Partner with data governance, architecture, system owners, business domains and cyber to align models to systems schemas, metadata management, business requirements, ownership, and certification/security. Optimise models for performance, quality and usability, ensuring scalable, future proof models are delivered. Collaborate with and lead work with Data Engineers/Architects on upstream transformations and data quality rules, ensuring end to end traceability, lineage and master data management. Collaborate with and lead/advise report developers and end users of the data (business/IT/data practitioners) to make effective use of the models. Support self service enablement: templates, guidance, and guardrails for analysts and report builders. Lead working groups and work with stakeholders to articulate business requirements and model development with IT and business domain leaders. Deliver complex, executive reports to educate and gain buy in and support for business requirements and global data model design. Lead programmes of work and ensure they are run effectively to time, quality standards and meeting budget requirements. Educate and train regional staff and provide templates and guidance on data modelling best practice, as the global lead for data modelling. Be able to lead and enable data modelling for AI/ML use cases by providing quality datasets and impactive data models and advise data scientists on engineering and modelling needs. Skills Strong data modelling expertise: dimensional modelling, business rules, dimensions; data patterns. Ability to define and govern metrics and model consistency across multiple products and source system integrations. SQL mastery and experience with transformation frameworks and testing/documentation practices. SQL, building Star Schema data models and ETL & DAX. Deeply skilled in BI, including semantic layers (e.g., Power BI semantic models) and performance/cost optimisation. Extensive skills in data quality, traceability and observability integrated into modelling workflows. Strong stakeholder skills to translate business requirements into robust data products. Effective communicator with strong influencing, negotiating, and relationship building skills. Ability to articulate modelling to executives. Ability to translate complex data into meaningful insight for non technical audiences. Able to work independently, manage competing priorities, and lead through change. Provide hands on technical guidance to delivery and data teams across data modelling as the global lead. High attention to detail, integrity, and commitment to ethical data use. Strong executive written documentation, planning, organisation, prioritisation and design governance, and discipline. Passionate about data and innovative to enable RES to stay ahead of and implement global best practice in modern, scalable and future proof data modelling. It is mandatory that you are highly skilled in global corporate service data modelling, including integrating multiple source systems. You must have knowledge and skills in IFS (RES's enterprise ERP system) and extensive skills in financial and human resources data. Qualifications and Experience Bachelor's degree in Data Analytics, Data Science, or a related field. Significant experience in analytics engineering, semantic modelling and BI/data modelling roles in a global setting. Evidenced high quality, significant quantifiable outcomes from delivering global human resources and finance data modelling. Providing high quality, consistent and highly maintained accurate global finance and HR views which are adopted by executives and used for ongoing decision making - with little re work and high success rate for maintenance year on year - future proof data models. Deep understanding of BI and semantic modelling patterns and how they fit into enterprise architecture, evidence through quantified outcomes of delivery. Proven delivery of reusable semantic layers that improved consistency and reduced duplicated logic across reports. Proven experience of delivering model that realises efficiency savings across global organisations through adoption of data from semantic models, reducing business domains teams manual work and efforts, enabling self service reporting across multiple systems and domains. Experience partnering with and leading Finance/HR and IT teams to define business requirements and modelling schemas and gaining sign off from senior personnel, including KPIs and reporting logic. In depth knowledge and practical implementation of compliance frameworks and global employment regulations as they relate to data modelling and analytics engineering. Knowledge and experience in employing global data standardisation frameworks for harmonising data definitions, taxonomies, and formats across regions. It is mandatory that you have proven experience in data modelling for IFS (RES's enterprise ERP system) and extensive experience in financial and human resources data, corporate services multiple system integration data architecture in a global context. Experience in AI/ML enablement and integration with data and analytics platforms. Strong communication and stakeholder engagement skills, alongside technical breadth in data modelling and analytics engineering. Extensive experience briefing executive leaders and running data and reporting programmes. Working knowledge and experience in AI/ML and automation, as they apply to data modelling, reporting and analytics. Strong executive/senior stakeholder skills to translate business requirements into robust data products. Highly effective communicator (verbal and written) with strong influencing, negotiating, and relationship building experience. Evidenced experience leading workshops and governance forums for data modelling/reporting with senior executives with high quality modelling outcomes. Provide hands on technical guidance to delivery and data teams across data modelling as the global lead. Experience as the technical modelling lead for an international organisation. 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.
12/07/2026
Full time
Job Summary This is a rare opportunity to join a newly created global data modelling lead role, in a growing central data and analytics team. Your key work will be to lead the design and build of governed, reusable global data models that translate enterprise data into business ready dimensions, facts and metrics for consistent reporting, self service reporting, analytics and AI/ML readiness. You will be the bridge between the data team, IT leaders and business leaders: understanding and defining requirements, shaping data products, modelling business logic, and enabling performant, well documented accurate data delivery at a global scale. This work relates predominantly in year one to corporate services data, specifically finance and human resources. You will be the global lead in RES for data modelling and analytics engineering, educating and training regional staff, providing templates and guidance on best practice. Lead working groups with the business/IT and define comprehensive business requirements from stakeholders. From the business requirements assess buy versus build options and if a data platform build is chosen then design the data model in conjunction with IT/data teams and business domain leaders. Once signed off, build, deliver and maintain a comprehensive, scalable data model and lead implementation, optimisation, and scalability. Accountabilities Design global data models aligned to agreed business definitions, KPIs and reporting departments in conjunction with executives, business domains and senior IT leaders. Develop and maintain metric definitions and calculation logic to ensure model consistency across dashboards and reports. Build, deliver and maintain curated data modelling and products with documentation, tests, and versioning. Partner with data governance, architecture, system owners, business domains and cyber to align models to systems schemas, metadata management, business requirements, ownership, and certification/security. Optimise models for performance, quality and usability, ensuring scalable, future proof models are delivered. Collaborate with and lead work with Data Engineers/Architects on upstream transformations and data quality rules, ensuring end to end traceability, lineage and master data management. Collaborate with and lead/advise report developers and end users of the data (business/IT/data practitioners) to make effective use of the models. Support self service enablement: templates, guidance, and guardrails for analysts and report builders. Lead working groups and work with stakeholders to articulate business requirements and model development with IT and business domain leaders. Deliver complex, executive reports to educate and gain buy in and support for business requirements and global data model design. Lead programmes of work and ensure they are run effectively to time, quality standards and meeting budget requirements. Educate and train regional staff and provide templates and guidance on data modelling best practice, as the global lead for data modelling. Be able to lead and enable data modelling for AI/ML use cases by providing quality datasets and impactive data models and advise data scientists on engineering and modelling needs. Skills Strong data modelling expertise: dimensional modelling, business rules, dimensions; data patterns. Ability to define and govern metrics and model consistency across multiple products and source system integrations. SQL mastery and experience with transformation frameworks and testing/documentation practices. SQL, building Star Schema data models and ETL & DAX. Deeply skilled in BI, including semantic layers (e.g., Power BI semantic models) and performance/cost optimisation. Extensive skills in data quality, traceability and observability integrated into modelling workflows. Strong stakeholder skills to translate business requirements into robust data products. Effective communicator with strong influencing, negotiating, and relationship building skills. Ability to articulate modelling to executives. Ability to translate complex data into meaningful insight for non technical audiences. Able to work independently, manage competing priorities, and lead through change. Provide hands on technical guidance to delivery and data teams across data modelling as the global lead. High attention to detail, integrity, and commitment to ethical data use. Strong executive written documentation, planning, organisation, prioritisation and design governance, and discipline. Passionate about data and innovative to enable RES to stay ahead of and implement global best practice in modern, scalable and future proof data modelling. It is mandatory that you are highly skilled in global corporate service data modelling, including integrating multiple source systems. You must have knowledge and skills in IFS (RES's enterprise ERP system) and extensive skills in financial and human resources data. Qualifications and Experience Bachelor's degree in Data Analytics, Data Science, or a related field. Significant experience in analytics engineering, semantic modelling and BI/data modelling roles in a global setting. Evidenced high quality, significant quantifiable outcomes from delivering global human resources and finance data modelling. Providing high quality, consistent and highly maintained accurate global finance and HR views which are adopted by executives and used for ongoing decision making - with little re work and high success rate for maintenance year on year - future proof data models. Deep understanding of BI and semantic modelling patterns and how they fit into enterprise architecture, evidence through quantified outcomes of delivery. Proven delivery of reusable semantic layers that improved consistency and reduced duplicated logic across reports. Proven experience of delivering model that realises efficiency savings across global organisations through adoption of data from semantic models, reducing business domains teams manual work and efforts, enabling self service reporting across multiple systems and domains. Experience partnering with and leading Finance/HR and IT teams to define business requirements and modelling schemas and gaining sign off from senior personnel, including KPIs and reporting logic. In depth knowledge and practical implementation of compliance frameworks and global employment regulations as they relate to data modelling and analytics engineering. Knowledge and experience in employing global data standardisation frameworks for harmonising data definitions, taxonomies, and formats across regions. It is mandatory that you have proven experience in data modelling for IFS (RES's enterprise ERP system) and extensive experience in financial and human resources data, corporate services multiple system integration data architecture in a global context. Experience in AI/ML enablement and integration with data and analytics platforms. Strong communication and stakeholder engagement skills, alongside technical breadth in data modelling and analytics engineering. Extensive experience briefing executive leaders and running data and reporting programmes. Working knowledge and experience in AI/ML and automation, as they apply to data modelling, reporting and analytics. Strong executive/senior stakeholder skills to translate business requirements into robust data products. Highly effective communicator (verbal and written) with strong influencing, negotiating, and relationship building experience. Evidenced experience leading workshops and governance forums for data modelling/reporting with senior executives with high quality modelling outcomes. Provide hands on technical guidance to delivery and data teams across data modelling as the global lead. Experience as the technical modelling lead for an international organisation. 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.
A forward-thinking data solutions company is looking for a global data modelling lead. This role requires strong expertise to design and implement global data models that support finance and HR functions. The successful candidate will lead documentation, stakeholder education, and establish best practices for robust data integration. The position is suited for those with a passion for leveraging data to enable insightful decisions and organizational efficiency. Candidates must have a background in data analytics, proven experience in data modelling, and the ability to communicate effectively with stakeholders across various levels.
24/06/2026
Full time
A forward-thinking data solutions company is looking for a global data modelling lead. This role requires strong expertise to design and implement global data models that support finance and HR functions. The successful candidate will lead documentation, stakeholder education, and establish best practices for robust data integration. The position is suited for those with a passion for leveraging data to enable insightful decisions and organizational efficiency. Candidates must have a background in data analytics, proven experience in data modelling, and the ability to communicate effectively with stakeholders across various levels.
RES is seeking a Data Analytics and AI Lead to own the design and delivery of analytics, data modelling, reporting, and AI-enabled solutions using Azure, Fabric, and Purview. This role will establish trusted, governed, and explainable data products, and lead automation efforts including Power Platform and data flows. Applicants should have a Bachelor's degree in data analytics or data science and extensive experience delivering high-value data solutions. Leadership skills and knowledge of AI governance frameworks are essential.
22/06/2026
Full time
RES is seeking a Data Analytics and AI Lead to own the design and delivery of analytics, data modelling, reporting, and AI-enabled solutions using Azure, Fabric, and Purview. This role will establish trusted, governed, and explainable data products, and lead automation efforts including Power Platform and data flows. Applicants should have a Bachelor's degree in data analytics or data science and extensive experience delivering high-value data solutions. Leadership skills and knowledge of AI governance frameworks are essential.
Data Analytics and AI Lead Job Summary The Data 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 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 Lead automation, including Power Platform, Dataverse, Microsoft365 Dynamics, and other tools Lead coding, vibe coding, LLMs, prompt engineering, Python, SQL, Power Automate, and data flows 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 Strong experience in automation, including Power Platform, Dataverse, Microsoft365 Dynamics, and other tools Strong experience in coding, vibe coding, LLMs, prompt engineering, Python, SQL, Power Automate, and data flows 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 Strong experience in automation, including Power Platform, Dataverse, Microsoft365 Dynamics, and other tools Strong experience in coding, vibe coding, LLMs, prompt engineering, Python, SQL, Power Automate, and data flows 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 Benefits Our competitive package offers a wide range of benefits and rewards. Equal Opportunity 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.
22/06/2026
Full time
Data Analytics and AI Lead Job Summary The Data 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 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 Lead automation, including Power Platform, Dataverse, Microsoft365 Dynamics, and other tools Lead coding, vibe coding, LLMs, prompt engineering, Python, SQL, Power Automate, and data flows 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 Strong experience in automation, including Power Platform, Dataverse, Microsoft365 Dynamics, and other tools Strong experience in coding, vibe coding, LLMs, prompt engineering, Python, SQL, Power Automate, and data flows 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 Strong experience in automation, including Power Platform, Dataverse, Microsoft365 Dynamics, and other tools Strong experience in coding, vibe coding, LLMs, prompt engineering, Python, SQL, Power Automate, and data flows 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 Benefits Our competitive package offers a wide range of benefits and rewards. Equal Opportunity 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.
Data Analytics and AI Lead Job Summary The Data 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 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 Lead automation, including Power Platform, Dataverse, Microsoft365 Dynamics, and other tools Lead coding, vibe coding, LLMs, prompt engineering, Python, SQL, Power Automate, and data flows 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 Strong experience in automation, including Power Platform, Dataverse, Microsoft365 Dynamics, and other tools Strong experience in coding, vibe coding, LLMs, prompt engineering, Python, SQL, Power Automate, and data flows 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 Strong experience in automation, including Power Platform, Dataverse, Microsoft365 Dynamics, and other tools Strong experience in coding, vibe coding, LLMs, prompt engineering, Python, SQL, Power Automate, and data flows 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 Benefits Our competitive package offers a wide range of benefits and rewards. Equal Opportunity 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.
22/06/2026
Full time
Data Analytics and AI Lead Job Summary The Data 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 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 Lead automation, including Power Platform, Dataverse, Microsoft365 Dynamics, and other tools Lead coding, vibe coding, LLMs, prompt engineering, Python, SQL, Power Automate, and data flows 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 Strong experience in automation, including Power Platform, Dataverse, Microsoft365 Dynamics, and other tools Strong experience in coding, vibe coding, LLMs, prompt engineering, Python, SQL, Power Automate, and data flows 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 Strong experience in automation, including Power Platform, Dataverse, Microsoft365 Dynamics, and other tools Strong experience in coding, vibe coding, LLMs, prompt engineering, Python, SQL, Power Automate, and data flows 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 Benefits Our competitive package offers a wide range of benefits and rewards. Equal Opportunity 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.
RES is seeking a Data Analytics and AI Lead to own the design and delivery of analytics, data modelling, reporting, and AI-enabled solutions using Azure, Fabric, and Purview. This role will establish trusted, governed, and explainable data products, and lead automation efforts including Power Platform and data flows. Applicants should have a Bachelor's degree in data analytics or data science and extensive experience delivering high-value data solutions. Leadership skills and knowledge of AI governance frameworks are essential.
22/06/2026
Full time
RES is seeking a Data Analytics and AI Lead to own the design and delivery of analytics, data modelling, reporting, and AI-enabled solutions using Azure, Fabric, and Purview. This role will establish trusted, governed, and explainable data products, and lead automation efforts including Power Platform and data flows. Applicants should have a Bachelor's degree in data analytics or data science and extensive experience delivering high-value data solutions. Leadership skills and knowledge of AI governance frameworks are essential.