Senior Data Engineer – Banking/Financial

Job Summary Lead the design and implementation of large-scale data engineering solutions within banking environments. Drive data platform modernization, migration, and regulatory initiatives while managing technical teams and collaborating with stakeholders to ensure robust, high-quality data delivery. Responsibilities • Design and implement large-scale data pipelines, ETL frameworks, and batch processing solutions to support enterprise data platforms. • Develop and optimize data integration processes using Python, PySpark, SQL, Hadoop HDFS, Spark, Hive, and Teradata technologies. • Lead Teradata-to-Hadoop/Data Lake migration projects, legacy platform modernization, technology refresh, and application decommissioning efforts. • Manage and optimize enterprise ETL platforms such as Talend, DataStage, or Informatica, including migration and performance tuning. • Apply data modeling, profiling, quality assurance, lineage tracking, and transformation techniques on large structured and unstructured datasets. • Provide technical leadership to large data engineering teams through solution design, code and design reviews, troubleshooting, delivery governance, and production support. • Design data architecture frameworks, CI/CD pipelines, and orchestration workflows using Autosys, Control-M, Jenkins, and Git. • Oversee enterprise data migration, job optimization, capacity planning, and production/BAU support in high-volume banking environments. • Deliver regulatory and risk-data initiatives aligned with AML, Fraud, MAS regulations, BCBS239, data quality, and critical data element lineage requirements. • Manage stakeholder relationships with banking technology teams, business analysts, infrastructure, data management, and senior clients to ensure successful technical solution delivery. Required competencies and certifications • Hands-on expertise in Python, PySpark, SQL, Hadoop HDFS, Spark, Hive, and Teradata technologies. • Experience with enterprise ETL platforms such as Talend, DataStage, or Informatica. • Proven technical leadership of large data engineering teams. • Experience in Teradata-to-Hadoop/Data Lake migration and legacy platform modernization. • Experience delivering regulatory or risk-data initiatives including AML, Fraud, MAS regulatory requirements, BCBS239, and data quality. Preferred competencies and qualifications • Experience within Banking/Financial Services, especially Retail Banking, Cards, AML, Fraud, Regulatory Reporting, or Data Warehouse environments. • Strong stakeholder management skills with cross-functional teams and senior client stakeholders. • Experience designing CI/CD pipelines and orchestration using Autosys, Control-M, Jenkins, and Git. • Experience with performance tuning, job optimization, capacity planning, and production/BAU support in high-volume banking environments.