The Careers are Better at Hungry Jack's! This is a critical technical leadership role responsible for shaping and delivering the organisation’s modern data platform while ensuring the stability and continuous improvement of business-as-usual (BAU) data operations. The role leads the design, implementation, and reliable running of the enterprise data ecosystem, balancing platform transformation, including the transition to Microsoft Fabric, with the day-to-day operation of pipelines, data services, and environments. It ensures data can be consistently captured, modelled, and activated across digital, finance, operational, and commercial domains. You will provide hands-on leadership to data engineers, uplift engineering capability, modernise legacy pipelines, and maintain high platform reliability through strong operational practices and clear prioritisation of BAU and delivery. Working closely with product, finance, marketing, HR, and other business stakeholders, this role ensures the data platform is scalable, trusted, and aligned to enabling better decisions and digital outcomes. Key Responsibilities: 1. Data Platform Leadership & Architecture • Lead the design and evolution of the enterprise data platform architecture under the guidance on Enterprise Architecture team. • Guide adoption of modern patterns, including lakehouse, scalable pipelines, and modular data modelling. • Ensure the platform supports digital analytics, customer data, operational reporting, and future growth. • Provide technical direction and architectural oversight across initiatives. 2. BAU Operations & Reliability • Ensure reliable operation of data pipelines and platform services. • Manage incident response, root cause analysis, and resolution. • Balance operational priorities with strategic delivery. • Establish monitoring, alerting, and operational standards. 3. Engineering Leadership & Capability Uplift • Provide day-to-day technical leadership and mentorship to data engineers. • Uplift team capability in modern tools (e.g., Fabric, dbt, cloud patterns). • Define and enforce coding, modelling, and deployment standards. • Foster a culture of ownership, accountability, and continuous improvement. 4. Delivery & Execution • Lead delivery of data initiatives across digital, marketing, and enterprise domains. • Ensure predictable delivery through clear prioritisation and technical guidance. • Remove blockers and coordinate across teams. 5. Stakeholder Engagement • Partner with product, digital, analytics, marketing, finance and business stakeholders. • Translate requirements into scalable technical solutions. • Manage expectations and navigate competing priorities. • Act as a trusted technical advisor. 6. Data Quality & Governance • Implement standards for data quality, data retention, lineage, and consistency. • Ensure data assets are trusted and fit for purpose. • Support governance and compliance requirements. 7. Fabric Implementation & Modernisation • Lead implementation and optimisation of Microsoft Fabric capabilities. • Drive migration from legacy ETL and warehouse environments. • Introduce modern engineering practices (e.g., modular pipelines, version control, automated testing). • Reduce technical debt and improve maintainability. What we are looking for: Essential: 10 years of progressive experience in data engineering, including leading platform modernisation, operating production systems, and guiding engineering teams. Bachelor’s degree in Computer Science, Software Engineering, Information Technology, Data Engineering, or a related technical discipline, or equivalent. Extensive experience in data engineering using Microsoft platform such as Azure Synapse, Azure Data Factory, Azure Data Lake, and MS Fabric Relevant experience in modern data toolsets such as dbt, MS Purview etc. Experience building and maintain semantic models Proven experience leading or acting as a senior technical lead. Strong experience supporting production data environments. Experience working with complex stakeholders and competing priorities. Experience mentoring or leading engineers. Deep experience with modern cloud data platforms and lakehouse architectures. Advanced SQL and strong programming capability. Experience implementing CI/CD, version control, and automated testing. Strong understanding of data modelling and pipeline design. Experience operating production data environments with monitoring and reliability practices. Ability to work across legacy and modern data ecosystems. Knowledge of Medallion Architecture/ Lakehouse/Data Warehouse in Fabric. Tooling: Strong SQL and PL/SQL skills, PySpark, Kusto Query Language, including complex queries and performance tuning Experience with Azure Data Factory, Azure SQL DW / Synapse, and Azure Data Lake Experience with enterprise reporting and visualisation tools such as SAP Business Objects, Tableau, and Power BI Experience with semantic modelling tools such as SAP BusinessObjects Information Design Tool Experience supporting Microsoft SQL Server environments, including legacy systems Understanding of ERP systems and Master Data concepts Familiarity with MDX or multidimensional modelling GitHub Actions, Terraform, and CoPilot C# and Python Azure Monitor and Grafana Desirable: Experience in the QSR industry AI assisted code generation Power Platform Fabric Data Engineer Associate Certification