Director, Cloud Data Solutions Lead

Sumitomo Mitsui Banking Corporation•Charlotte, NC

About The Position

The Cloud Data Solutions Lead oversees and manages cross-functional and internal projects to design and build enterprise data assets, including data lakes, and implement cloud-based data solutions using Azure services such as Azure Data Factory and Databricks. The role also establishes operational discipline for project execution and supports strategic initiatives to standardize data and enable business analytics, including risk and regulatory reporting for the bank. The position designs, develops, and deploys cloud data solutions for risk, regulatory, finance, and compliance projects, and contributes to on-premises-to-cloud migration initiatives. It works with business stakeholders, product managers, architects, engineers, information analysts, data stewards, technology teams, and third-party companies to understand needs, coordinate integrations, develop enterprise-grade platforms, and deliver accurate and useful outcomes. The role provides technical guidance, owns projects end to end, and leads and mentors junior team members.

Requirements

  • 10+ years of software development experience in enterprise applications.
  • Extensive experience with cloud solutions, specifically Azure and Databricks.
  • Experience with Azure cloud services, including Azure Data Factory, Gen 2, Azure Databases, Functions, and Databricks.
  • Strong knowledge of Python, Java, or similar high-level server-side languages.
  • Advanced working SQL knowledge on relational databases, preferably MS SQL Server and databases on Azure cloud.
  • Experience designing and architecting distributed systems, containerization, Web APIs, and gateway management.
  • Experience with the DevOps lifecycle, including Git and Jenkins.
  • Experience with Jira and Confluence.
  • Experience with REST web services and microservice architecture.
  • Good understanding of ETL/ELT.
  • Experience with Databricks cluster configuration and Unity Catalog repository configuration.
  • Strong program and project management skills.
  • Strong communication and relationship-building competencies.
  • Ability to work with business and technology stakeholders to deliver data solutions.

Nice To Haves

  • Experience in the financial services industry, preferably on data-heavy systems.
  • Bachelor’s or master’s degree in computer science or information systems preferred.

Responsibilities

  • Oversee and manage cross-functional and internal projects involving enterprise data assets, data lakes, and cloud-based data solutions.
  • Design, develop, and deploy cloud data solutions for risk, regulatory, finance, and compliance projects.
  • Contribute to the bank’s on-premises-to-cloud migration initiative.
  • Work with business teams, product managers, and other stakeholders to understand requirements, needs, and process gaps.
  • Coordinate with IT systems architects, database administrators, cybersecurity, platform, APIM, Azure DevOps, and support teams to meet application and platform needs.
  • Coordinate application integrations with the broader company software ecosystem.
  • Participate in development meetings to align priorities and objectives, assign tasks, and share project experiences and challenges.
  • Build large-scale batch and real-time data pipelines on Azure cloud data-processing frameworks.
  • Partner with architects, engineers, information analysts, business stakeholders, and technology stakeholders to develop and deploy enterprise-grade data platforms.
  • Provide technical guidance on technology implementation and architectural changes.
  • Analyze and design Azure technical solutions to address business needs.
  • Develop, test, and modify software to improve data platform and application efficiency.
  • Own projects end to end, coordinating business stakeholders, IT teams, data stewards, and third-party companies.
  • Integrate data from multiple sources and ensure data quality and accessibility standards are met.
  • Enable streaming data use cases and standard design patterns in a big data environment.
  • Review and provide feedback on core code changes and support production deployment.
  • Lead and mentor junior team members.
  • Maintain operational discipline and support day-to-day project execution.
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