Risk Data Modeler III
Listed on 2026-08-17
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IT/Tech
Data Engineering, Data Analyst, Information Security & Data Protection
Bank Of America Data Modeler
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!
This job is responsible for driving efforts to develop and deliver complex data solutions to accomplish technology and business goals. Key responsibilities include leading code design and delivery tasks with the integration, cleaning, transformation and control of data in operational and analytical data systems. Job expectations include liaising with vendors and working with stakeholders and Product and Software Engineering teams to implement data requirements, analyzing performance, and researching and troubleshooting issues within system engineering domains.
A series of strategic projects and regulatory projects (examples, Strategic Risk and PnL [SRPL], Fundamental Review of the Trading Book [FRTB]) in global markets risk area would require senior data modeler with data modeling, data dictionary, data analysis skills. This experienced data professional should be able to interpret business requirements, high level data flows and convert into data elements and data models.
The risk data modeler would work in a data horizontal team that are responsible for database architecture, database platforms, data models, performance engineering and database platform related security vulnerabilities across Global Market Risk Technology (GMRT) and Counter party Credit Risk Technology (CCRT). The risk data modeler would work closely with the application development teams, business stakeholders, technology infrastructure database administrators to execute projects that are critical to the LOBs and technology partners.
Responsibilities:
- Leads story refinement and delivery of requirements through the delivery lifecycle and assists team members in resolving technical complexities
- Codes complex solutions to integrate, clean, transform, and control data, builds processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management, assembles complex data sets, and communicates required information for deployment
- Leads documentation of system requirements, collaborates with development teams to understand data requirements and feasibility, and leverages architectural components to develop client requirements
- Leads testing teams to develop test plans, contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies test issues and errors, and leads triage of underlying causes
- Leads work efforts with technology partners and stakeholders to close gaps in data management standards adherence, negotiates paths forward by thinking outside the box to identify and communicate solutions to complex problems, and leverages…
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