Data Engineer, Vice President

SMBC • Charlotte, NC

4d • 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, auditable, regulatory-compliant data platforms on Databricks. The work supports end-to-end data sourcing, CCAR model development and execution, data adjustments, result overlays, and attestation workflows.

The role collaborates with Finance, Risk, Data Management, and Model Development teams to build data engineering solutions that improve regulatory reporting processes and operational efficiency. It also involves applying AI/ML capabilities to data quality monitoring, anomaly detection, intelligent automation, and operational insights, as well as supporting releases and production operations.

SMBC uses a hybrid workforce model that provides employees the opportunity to work from home and from an SMBC office. Employees must live within a reasonable commuting distance of their office location. The specific hybrid schedule is discussed during the interview process; hybrid work may not be permitted for certain roles.

Requirements

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

What This Job Offers

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