Data Modeller / Analytics Engineer

TL;DR

Data Modeller / Analytics Engineer (BI): Lead the design and build of governed, reusable global data models translating enterprise data into business-ready dimensions, facts and metrics for reporting, analytics and AI/ML readiness with an accent on corporate services data in finance and human hirify.globalources. Focus on defining business requirements, optimizing models for performance and scalability, and enabling self-service reporting across global teams.

Location: United Kingdom, Kings Langley

Company

World's largest independent renewable energy company guided by a vision to create affordable, zero-carbon energy for everyone.

What you will do

• Design global data models aligned to business definitions, KPIs and reporting needs in collaboration with executives, business domains and IT leaders.
• Develop and maintain metric definitions, calculation logic, and curated data products with documentation, tests and versioning.
• Partner with data governance, architecture, system owners and cyber teams to align models with schemas, metadata and security standards.
• Optimize models for performance, quality and usability while collaborating with data engineers on transformations and data quality rules.
• Lead working groups to articulate requirements, assess buy vs build options, and deliver scalable data models.
• Educate and train regional staff on data modelling best practices as the global lead, enabling AI/ML use cases.

Requirements

• Location: United Kingdom, Kings Langley
• Strong data modelling expertise including dimensional modelling, business rules, dimensions and data patterns; mandatory skills in IFS ERP system and financial/HR data integration.
• SQL mastery, experience with transformation frameworks, Star Schema, ETL, DAX, BI semantic layers (e.g., Power BI) and performance optimization.
• Significant experience in analytics engineering and BI/data modelling in global settings with quantifiable outcomes in finance/HR data delivery.
• Deep understanding of compliance frameworks, global employment regulations and data standardization for harmonizing definitions across regions.
• Proven stakeholder skills to translate business requirements into data products, lead workshops and brief executives.

Nice to have

• Experience in AI/ML enablement and integration with data platforms.
• Working knowledge of automation in data modelling and reporting.

Culture & Benefits

• Competitive package with wide range of benefits and rewards.
• Investment in personal and professional growth with learning opportunities from global network.
• Diverse workforce celebrating differences in ethnicity, culture, gender, nationality and backgrounds.
• Rewarding work making real impact on world's toughest problems in renewable energy.