Key competencies

• Strong enterprise data architecture capability with experience defining target-state architectures, modernization roadmaps, and scalable data platform strategies.
• Deep understanding of cloud-native data ecosystems, distributed processing frameworks, data lakes, medallion architecture, Apache Airflow, Databricks Workflows, and modern data engineering practices.
• Strong expertise in data warehousing, dimensional modelling, ETL/ELT frameworks, metadata management, lineage, reconciliation, and enterprise data governance.
• Proven ability to modernise complex legacy and monolithic data environments into scalable, resilient, and modular architectures.
• Strong understanding of financial services, capital markets, regulatory reporting, and compliance-driven data architectures.
• Expertise in designing highly available, scalable, secure, and performance-optimized enterprise data platforms.
• Strong knowledge of ...