Data Modeller / Analytics Engineer

RES

About The Position

Do you want to work to make Power for Good? We're the world's largest independent renewable energy company. We're guided by a simple yet powerful vision: to create a future where everyone has access to affordable, zero carbon energy. We know that achieving our ambitions would be impossible without our people. Because we're tackling some of the world's toughest problems, we need the very best people to help us. They're our most important asset so that's why we continually invest in them. RES is a family with a diverse workforce, and we are dedicated to the personal professional growth of our people, no matter what stage of their career they're at. We can promise you rewarding work which makes a real impact, the chance to learn from inspiring colleagues from across a growing, global network and opportunities to grow personally and professionally. Our competitive package offers a wide range of benefits and rewards. 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 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 Key accountabilities include but are not limited to: 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.

Requirements

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.
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 realise 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 standardization frameworks for harmonizing 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 of 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.

Responsibilities

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.