Senior Risk Developer (Python/Azure)

Sumitomo Mitsui Banking Corporation•Charlotte, NC

1d•Hybrid

About The Position

SMBC Group is a top-tier global financial group. Headquartered in Tokyo and with a 400-year history, SMBC Group offers a diverse range of financial services, including banking, leasing, securities, credit cards, and consumer finance. The Group has more than 130 offices and 80,000 employees worldwide in nearly 40 countries. Sumitomo Mitsui Financial Group, Inc. (SMFG) is the holding company of SMBC Group, which is one of the three largest banking groups in Japan. SMFG’s shares trade on the Tokyo, Nagoya, and New York (NYSE: SMFG) stock exchanges. In the Americas, SMBC Group has a presence in the US, Canada, Mexico, Brazil, Chile, Colombia, and Peru. Backed by the capital strength of SMBC Group and the value of its relationships in Asia, the Group offers a range of commercial and investment banking services to its corporate, institutional, and municipal clients. It connects a diverse client base to local markets and the organization’s extensive global network. The Group’s operating companies in the Americas include Sumitomo Mitsui Banking Corp. (SMBC), SMBC Nikko Securities America, Inc., SMBC Capital Markets, Inc., SMBC MANUBANK, JRI America, Inc., SMBC Leasing and Finance, Inc., Banco Sumitomo Mitsui Brasileiro S.A., and Sumitomo Mitsui Finance and Leasing Co., Ltd. JOB SUMMARY:Senior Risk Developer (VP level) responsible for building and operating enterprise risk technology solutions that enable risk analytics, automation, and decision intelligence. This role designs and optimizes large-scale data pipelines and risk data products on Azure Databricks, develops SQL and Python services, and industrializes AI and ML models using governed lifecycle controls (including MLflow) and CI/CD. The position partners closely with Risk, Data Science, Engineering, and Product stakeholders to translate risk requirements into secure, scalable, auditable platforms and user-facing applications that support enterprise risk management outcomes. Reporting is within the Risk Technology organization to designated technology leadership, with accountability for end-to-end delivery from design through production support under SDLC controls.

Requirements

10+ years of data engineering or software development experience in financial services.
Advanced hands-on expertise with Azure Databricks and core Azure services used in eventing, monitoring, and integration (Azure Functions, Azure Data Lake Storage, Azure Event Grid, Azure Log Analytics, Azure Monitor, Azure Service Bus).
Strong programming and database skills: Python, SQL (SQL Server, T-SQL, stored procedures), and working knowledge of Oracle and PL-SQL; R exposure where relevant to analytics workflows.
Demonstrated experience building and operating AI and ML solutions across the model lifecycle, including deployment and production support.
Hands-on experience with Databricks MLflow for model tracking, experimentation, and governance.
Experience designing or implementing prompt-based AI agents or AI-assisted workflows in production or near-production settings.
Proficiency with Azure DevOps and CI/CD practices applied to data pipelines and model deployments.
Modern UI development capability, including React, and integration patterns between front-end applications and backend and data services.
Experience leading development efforts and collaborating in Agile delivery models.
Strong analytical problem-solving skills applied to risk data management and risk analytics use cases.
Strong stakeholder management and communication skills, including the ability to explain technical solutions to non-technical audiences.

Nice To Haves

Power BI experience for visualization and dashboarding.
Power Apps exposure for workflow automation and business process integration.
Domain familiarity with financial institution risk analytics (market risk, credit risk, enterprise risk).
Familiarity with model risk management practices and regulatory expectations for AI and ML models.

Responsibilities

Architect, develop, and maintain scalable risk data pipelines and curated datasets using Azure Databricks to support enterprise risk management frameworks.
Engineer and optimize data ingestion, transformation, storage, and retrieval solutions using SQL and Python with a focus on performance, reliability, and auditability.
Build, deploy, and operate AI and ML models for risk analytics, including experimentation, versioning, lineage, and governance using Databricks MLflow.
Design and implement prompt-based AI agents and AI-driven workflows to improve risk analysis, validation, monitoring, and decision support.
Implement and enforce CI/CD practices for risk models, pipelines, and applications, ensuring controlled promotion, rollback readiness, and version control.
Apply SDLC standards across build and release activities, including secure coding, testing discipline, documentation, and compliance with model governance and quality guidelines.
Partner with risk analysts, data scientists, and business stakeholders to define requirements and deliver scalable, user-centered risk technology solutions.
Develop user-facing risk applications and dashboards using modern UI frameworks (including React), integrating backend services and AI and ML outputs for interactive, near real-time insights.
Collaborate with UI/UX and front-end teams to deliver responsive, intuitive experiences that drive stakeholder adoption and reduce operational friction.
Identify and deliver process improvements that increase efficiency, scalability, and resilience of risk data processing, model execution, validation, monitoring, and reporting.
Lead and influence engineering delivery in an Agile environment, promoting engineering excellence, continuous improvement, and practical innovation.
Communicate architecture, tradeoffs, and delivery status effectively to technical and non-technical stakeholders, including senior leadership.