Risk Data Modeler III

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We drive Responsible Growth and deliver for our clients, teammates, communities, and shareholders every day. Our inclusive workplace supports teammates’ physical, emotional, and financial wellness through affordable, competitive, and flexible benefits. We value diverse perspectives shaped by military service, community college education, and varied work and life experiences, fostering resilience, leadership, and innovation.

Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development, with clear in-office expectations and flexibility based on role-specific responsibilities and business needs.

About the Role

This role drives 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. The role involves working on strategic and regulatory projects (e.g., Strategic Risk and PnL [SRPL], Fundamental Review of the Trading Book [FRTB]) in the global markets risk area, requiring a senior data modeler with expertise in data modeling, data dictionary, and data analysis.

The risk data modeler will work in a data horizontal team responsible for database architecture, database platforms, data models, performance engineering, and database security vulnerabilities across Global Market Risk Technology (GMRT) and Counterparty Credit Risk Technology (CCRT). The role involves close collaboration with application development teams, business stakeholders, and technology infrastructure database administrators to execute critical projects.

Responsibilities

• Leads story refinement and delivery of requirements through the delivery lifecycle; 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; leverages architectural components to develop client requirements.
• Leads testing teams to develop test plans; contributes to existing test suites including integration, regression, and performance testing; 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 identifying and communicating solutions to complex problems.
• Leads complex information technology projects to ensure on-time delivery and adherence to release processes and risk management; defines and builds data pipelines to enable data-informed decision making.
• Mentors Data Engineers to enable continuous development and monitors key performance indicators and internal controls.

Requirements

• 10+ years of applicable experience in data modeling, data architecture, and data engineering.
• Familiarity with data modeling tools like Power Designer.
• Database knowledge on relational and unstructured data; experience with RDBMS and Hadoop technologies such as DB2, Oracle, Sybase, Impala, Kudu, and Iceberg.
• Data architecture skills including overall data flow management, authoritative data source management, data discovery, data dictionary, and data lineage.
• Data engineering skills: building data pipelines, data ingestion/retrieval, and distributed data systems.

Qualifications

• Database, SQL, performance tuning, scripting, and coding in Python/Shell/Perl.
• Experience with messaging systems like Kafka.
• Domain knowledge in finance and risk is preferred.
• Skills in analytical thinking, application development, data management, DevOps practices, solution design, Agile practices, collaboration, decision making, risk management, test engineering, architecture, business acumen, data quality management, financial management, and solution delivery process.

Schedule

1st shift (United States of America), 40 hours per week.