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Provides senior executive sponsorship for complex APAC client transformation programmes. Builds trusted executive relationships, supports governance and escalations, aligns client and organizational priorities, removes cross-functional barriers, and facilitates decisions across globally distributed teams. The role strengthens strategic client relationships, supports commercial discussions, promotes delivery transparency, and develops a repeatable executive engagement model without owning day-to-day delivery or programme workstreams.

Leads requirements discovery, stakeholder alignment, data analysis, workstream planning, governance, testing coordination, and cutover readiness for complex data transformation programs. Coordinates teams across data management, engineering, operations, testing, and client stakeholders while maintaining requirements traceability, RAID and RAG reporting, dependency management, data validation, and delivery quality.

Design and maintain scalable financial data models on Databricks using Delta Lake and Lakehouse architecture. Profile and validate index, pricing, reference, ESG, and research datasets; identify data-quality and schema issues; define source-to-target mappings; and collaborate with Data Engineering on ETL/ELT implementation. Use Unity Catalog for governance and lineage, document data structures and rules, test models before production, and update them as provider schemas change.

Own client-facing implementation projects from mobilization through production deployment. Responsibilities include project planning, governance, scope and change control, risk and issue management, stakeholder communication, delivery coordination, UAT, deployment readiness, and transition to steady-state operations. The role coordinates cross-functional teams, maintains project documentation and status reporting, manages client expectations, and applies AI-enabled tools to improve project management efficiency.

Design, build and operate scalable Databricks/PySpark data pipelines to ingest, transform and validate financial vendor data into production-ready datasets, partnering with product and client teams to meet quality and timeline requirements.