CCAR Data Engineer, Associate

SMBC Group is a top-tier global financial group headquartered in Tokyo with a 400-year history, offering a diverse range of financial services including banking, leasing, securities, credit cards, and consumer finance. The Group operates over 130 offices and employs 80,000 people worldwide across nearly 40 countries. In the Americas, SMBC Group serves corporate, institutional, and municipal clients through entities such as Sumitomo Mitsui Banking Corp. (SMBC), SMBC Nikko Securities America, Inc., and SMBC Capital Markets, Inc.

About the role

SMBC is driving a major Digital Transformation initiative across its Americas Division, focusing on modernizing technology platforms, enhancing data-driven decision-making, and supporting business growth. As part of this transformation, we are seeking a talented Data Engineer to join the Regulatory Reporting & CCAR Technology Team. This role involves developing scalable data platforms on Databricks to support end-to-end data sourcing, CCAR model execution, data adjustments, result overlays, and attestation workflows. The position requires collaboration with Finance, Risk, Data Management, and Model Development teams to deliver innovative, regulatory-compliant data engineering solutions.

Responsibilities

• Design, develop, and support scalable data pipelines using Databricks, PySpark, Python, SQL, and Delta Lake.
• Build and maintain data sourcing and ingestion frameworks for CCAR, Stress Testing, and Regulatory Reporting.
• Develop and support platforms for CCAR model execution, including PPNR, Balance Sheet, RWA, and other risk models.
• Implement data quality controls, reconciliation processes, lineage tracking, and audit capabilities.
• Develop solutions for data adjustments, management overlays, business overrides, and exception management workflows.
• Build and enhance attestation, approval, and sign-off workflows for regulatory reporting governance.
• Partner with Finance, Risk, and Regulatory Reporting stakeholders to deliver business-critical solutions.
• Leverage AI/ML capabilities for data quality monitoring, anomaly detection, intelligent automation, and operational insights.
• Support CI/CD, production releases, troubleshooting, performance tuning, and operational support activities.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.
• 7+ years of experience in Data Engineering, Data Platform Development, or Analytics Engineering.
• Strong hands-on experience with: Azure Data Factory, Databricks, PySpark, Python, SQL, Delta Lake, GitHub, and CI/CD.
• Experience building cloud-native and distributed data processing solutions.
• Strong understanding of ETL/ELT architectures, data modeling, data governance, and data quality frameworks.
• Knowledge of AI/ML concepts, machine learning lifecycle management, and model operationalization.
• Excellent analytical, problem-solving, communication, and stakeholder management skills.

Preferred Qualifications

• Experience supporting CCAR, FR Y-14 Regulatory Reporting, Stress Testing, Capital Planning, Risk Management, or Finance Technology initiatives.
• Experience developing solutions for: data sourcing and reconciliation, model execution platforms, data adjustments and result overlays, attestation and workflow management.
• Experience with MLflow, Databricks Workflows, Azure Data Factory, Azure SQL, Azure Functions, REST APIs, and Azure Cloud Services.
• Experience migrating analytical models from R to Python and deploying AI/ML solutions into production.
• Knowledge of model governance, model risk management, audit controls, and regulatory compliance requirements.
• Experience working in highly regulated financial services environments with strong governance and audit requirements.

Schedule

SMBC’s employees participate in a Hybrid workforce model, requiring employees to live within a reasonable commuting distance of their office location. Hybrid work schedules will be discussed during the interview process. Certain roles, including FINRA-registered positions, may require full-time in-office attendance.