Data Engineer, Vice President

Sumitomo Mitsui Banking Corporation • Charlotte, NC

6d • Hybrid

About The Position

SMBC is undertaking a Digital Transformation initiative across its Americas Division to modernize technology platforms, improve data-driven decision-making, and support business growth. The Data Engineer will join the Regulatory Reporting and Finance Technology Team and develop scalable data platforms on Databricks to support end-to-end data sourcing, CCAR model development and execution, data adjustments, result overlays, and attestation workflows. The role requires expertise in Databricks, PySpark, Python, and AI/ML to deliver robust, auditable, and regulatory-compliant solutions in collaboration with Finance, Risk, Data Management, and Model Development teams.

The position designs and supports data pipelines and ingestion frameworks; platforms for CCAR model execution; data quality, reconciliation, lineage, and audit controls; adjustment and exception workflows; and regulatory reporting governance workflows. It also contributes to AI/ML-enabled monitoring and automation, CI/CD and production releases, troubleshooting, performance tuning, and operational support.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.
• 12+ 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.

Nice To Haves

• 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, and 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.

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 for data quality monitoring, anomaly detection, intelligent automation, and operational insights.
• Support CI/CD, production releases, troubleshooting, performance tuning, and operational support activities.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior