• The successful candidate will be responsible for designing, building, and maintaining the organisation’s data infrastructure to support high-quality Business Intelligence (BI) and analytics across all departments. He/She will ensure that data from operational and financial systems is reliably captured, cleaned, structured, and transformed into intuitive dashboards and analytical tools that empower data-driven decision-making across the group’s properties and leadership teams.

Key Responsibilities.

• Design, build, and maintain ETL/ELT data pipelines across multiple systems (PMS, POS, CRM, procurement, HR, financial systems).
• Develop and optimise data models (star/snowflake schemas) and maintain the data warehouse/data lake as the organisation’s single source of truth.
• Ingest, clean, validate, and monitor data quality, ensuring consistency, completeness, and reliability across all datasets.
• Build and enhance BI dashboards and reports (Power BI, Tableau, Looker, Qlik) that are user-friendly, commercially relevant, and visually intuitive.
• Translate business questions into BI requirements, ensuring accurate SQL/DAX logic and consistently applied data definitions.
• Collaborate with Finance, Operations, Commercial, HR, and Technology teams to understand data needs and deliver actionable technical solutions.
• Create reusable data assets such as semantic layers, data marts, feature stores, and validated master datasets.
• Document data flows, transformation logic, system architecture, and maintain an updated data catalogue.
• Ensure data governance, security compliance, and implement best practices for metadata management.
• Automate repetitive data tasks, identify improvement opportunities, and drive continuous enhancement of BI and analytics systems.

Key Qualifications.

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• Minimum of 5 years’ experience in data engineering, BI development, or backend data architecture roles.
• Strong experience designing ETL/ELT pipelines and working with modern data warehousing technologies.
• Proficiency in SQL, Python, and data modelling concepts (dimensional modelling, semantic layers).
• Hands-on experience with BI tools such as Power BI, Tableau, Looker, or Qlik.
• Strong understanding of database systems (SQL & NoSQL) and cloud data environments.
• Experience managing master datasets and integrating data across multiple operational systems.
• Excellent analytical skills with the ability to translate business needs into technical solutions.
• Strong documentation skills and familiarity with data catalogues, data lineage, and governance frameworks.
• Experience working with automation, process optimisation, and workflow efficiencies