-Design and maintain scalable, secure data lake and lakehouse solutions using Azure Data Lake, Databricks and Delta Lake — built to support real-time insight, advanced analytics and AI/ML at enterprise scale.
-Develop and optimise batch and streaming ETL/ELT pipelines using Azure Data Factory, PySpark, SQL, Apache Spark and Airflow, integrated with modern tooling like dbt and Git-based CI/CD.
-Implement data cataloguing, lineage tracking and governance frameworks through Collibra, ensuring data across the enterprise is discoverable, well-documented and compliant.
-Own the day-to-day leadership, coaching and development of the Data Engineering team within the Global Data Office — supporting recruitment, performance management, skills growth and the adoption of engineering best practices.
-Work closely with Data Office leadership to define engineering strategy, support delivery planning, and build a high-performing, collaborative engineering culture across a geographically dispersed team.
-Monitor and tune data jobs for performance, scalability and cost; embed data validation, logging and monitoring to catch issues early and keep the platform reliable.