VP - Lead Data Engineer (Big Data)
Summary
Lead a bank's enterprise data engineering function in Singapore, architecting large-scale platforms (Databricks, Snowflake, BigQuery, lakehouse formats like Iceberg/Delta Lake/Hudi) and NLP pipelines over unstructured data, supporting regulatory reporting, risk, and analytics.
Lead initiatives to unlock business value from unstructured data sources including documents, customer interactions, regulatory publications, policies, and operational records. Design NLP-enabled data pipelines that support:Document classificationKnowledge extractionText analyticsSemantic searchAutomated summarizationRegulatory intelligence Establish end-to-end frameworks covering data ingestion, preprocessing, model evaluation, explainability, and operational deployment. Ensure AI-generated outputs are traceable, auditable, and suitable for regulatory scrutiny. Establish robust controls for:Data qualityData reconciliationData validationData certification Implement metadata management, lineage, and impact analysis capabilities. Drive the governance and management of Critical Data Elements (CDEs) across business domains. Experience
12+ years of experience in enterprise data engineering, analytics, and data platform delivery. Significant leadership experience within banking, financial services, or other highly regulated industries. Proven track record delivering enterprise-scale data transformation and modernization initiatives. Technical Expertise with Strong hands-on experience with: Databricks, Snowflake Apache Spark, Iceberg, Delta Lake, Apache Hudi Trino / Presto Hive SQL BTEQ Working knowledge of: Pandas NumPy Interested candidates please email your latest resume to (HIDDEN TEXT)