Internal Data Lead

- Define the right fit technology stack for our enterprise data warehouse, covering analysis, design and implementation. - Define modelling standards (star schemas, semantic layers, reusable datasets). - Ensure performance, scalability and cost efficiency. - Build with long-term growth in mind. - Design and oversee ETL pipelines from ERP, CRM and operational systems. - Implement data quality controls, testing and monitoring. - Design and implement a right-fit data governance structure, enabling trusted data sets & reporting. - Introduce DataOps practices (version control, deployment standards). - Act as technical authority across the data estate. - Lead and direct an established offshore data engineering partner. - Set technical standards and review deliverables. - Own outcomes and quality of delivery. - Translate commercial and operational requirements into scalable data models. - Improve reporting consistency and data reliability. - Raise data literacy and challenge inconsistent practices. - Establish a governed semantic layer to enable safe, scalable self-service reporting across the business. - Design certified datasets and reusable data models to reduce duplication and inconsistent KPI definitions. - Own the building of high-value dashboards (e.g. financial, operational, commercial). - Establish reporting standards and consistent KPI definitions. - Reduce reliance on ad-hoc reporting and Excel through scalable, governed datasets.