VP/Director, Global Markets Data Incident Management
Bank of America
- Location
- New York
- Work model
- On-Site
- Level
- Staff
- H-1B history
- 278 approvals (FY2023)
- Posted
- Aug 26, 2026
Skills
About this role
Job Description
At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits. We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve. Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
Job Description
Global Markets Data Management is responsible for establishing and executing data management strategy and data governance for GM. The team works closely with other groups within GM, other lines of business and Enterprise functions. The team drives strategic initiatives and projects in the areas of data management and governance. The GM Data Incident Management team within GMDM is accountable for remediation of data incidents concerning consumption of GM Data. The team triages, prioritizes and remediates GM data incidents, working closely with other groups within GM and other lines of business, including Technology, support partners (in particular Market Risk and Counterparty Credit Risk) and Enterprise functions at all levels. The ideal candidate will have expert knowledge of GM products, data structures, processes, strong project management skills, and experience in running data management projects, and understanding Bank of America’s policies, standards, and procedures.
Responsibilities
Manage data incident triage with key stakeholders. Act as a liaison between technical and non-technical stakeholders, translating complex data concepts into actionable insights. Provide SME knowledge and interface with various technology, quantitative, and business groups, representing providers and consumers of GM’s data. Deliver insights from large datasets, design data solutions, and communicate solutions to stakeholders. Strong ability to conceptualize business requirements as functions and data models. Effectively manages multiple concurrent initiatives and competing priorities, consistently delivering high-quality outcomes in a fast-paced and complex environment. Demonstrates exceptional organizational and execution skills, balancing strategic objectives, operational responsibilities, and time-sensitive deliverables while maintaining a high standard of accuracy and accountability. Conducts comprehensive analyses of complex data quality issues, performing detailed root-cause investigations to identify underlying drivers, assess business impact, and develop sustainable remediation strategies. Provides leadership in the identification, prioritization, and resolution of data quality issues, driving cross-functional collaboration, stakeholder alignment, and timely execution of corrective actions. Develops automated reporting and monitoring solutions using Python, SQL, and HUE/Oozie workflows to improve efficiency, scalability, and data