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.