M
Not Specified Permanent

White Plains, New York · USA job

General Ledger Technology - Executive Director

Morgan Stanley

White Plains, New York

Job description

Overview

In this role you lead the global GLRD Technology function within Finance Technology, shaping strategy and delivering modern, data-driven platforms. You partner with Finance leadership to transform reference data, workflows, and AI-enabled processes across the firm. You'll build and mentor a high-performing, global engineering team, driving scalability, data quality, and operational control. This is a chance to impact how Morgan Stanley manages books, records, and financial data at scale.

Compensation / Benefits
  • attractive and comprehensive employee benefits and perks
  • ample opportunity to move about the business
  • supportive and empowering culture
Responsibilities
  • Manage the GLRD Technology team on a day-to-day basis
  • Define and execute the global GLRD technology strategy
  • Collaborate with Finance Reference Data leadership on priorities and transformation
  • Lead modernization of GLRD systems through automation and AI
  • Build and develop a high-performing global engineering team
  • Oversee architecture, design, development, testing, and deployment of GLRD platforms
  • Ensure system scalability, data quality, resiliency, and control
  • Promote best practices in workflow automation, DevOps, and data engineering
Key requirements
  • Finance domain expertise and experience in Finance Technology
  • Led teams of 15+ technologists in financial services or complex enterprises
  • Hands-on engineering leadership and problem-solving
  • Strong data engineering and data modelling experience
  • Excellent communicator with broad stakeholder influence
  • Strong listening, influencing, and relationship-building abilities
  • Highly organized, flexible, and able to operate in a fast-paced environment
  • Proven people manager with experience growing and motivating teams
  • Ability to manage large numbers of consumers with evolving requirements
  • Excellent communication
  • Strong listening and relationship-building
  • Adaptability and flexibility
  • Data engineering
  • Data modelling
  • Workflow automation

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