Data Steward – Data Operations (NY)

KBRA Data Management is part of the Technology department and works closely with the analytical teams to support the ratings process, improve data quality, and ensure compliance with internal policies and regulatory requirements.

The Data Operations team provides operational support throughout the rating lifecycle by creating and maintaining entities, transactions, securities, identifiers, and ratings data in KBRA's systems. This position is a mid-level Data Steward role, intended for individuals who have progressed beyond entry-level responsibilities and are capable of independently processing both standard and complex rating requests while supporting continuous process improvements.

The successful candidate will work collaboratively with analytical teams, Corporate Assessments, Electronic Publishing, Compliance, and Technology to ensure accurate, timely, and complete data supporting KBRA's ratings.

• Process standard and complex analytical rating requests independently, following established Standard Operating Procedures (SOPs).
• Research, analyze, and resolve atypical data scenarios that require judgment beyond documented procedures.
• Create and maintain entities, transactions, securities, ratings, identifiers (CUSIP, ISIN, LEI, etc.), and reference data throughout the rating lifecycle.
• Analyze internal analytical documentation and external reference sources to determine appropriate data updates.
• Perform confirmed data corrections and ad hoc data updates while maintaining high data quality standards.
• Participate in data quality initiatives, data profiling, reconciliation activities, and operational improvement projects.
• Assist with automation initiatives and process improvement efforts.
• Document new or updated operational procedures and maintain process documentation in Confluence.
• Investigate and resolve data discrepancies in collaboration with analytical teams and internal stakeholders.
• Support workflow coordination and ensure timely processing of rating activities.
• Identify opportunities to apply AI and automation to streamline manual processes, improve data quality, and enhance operational productivity.

• Minimum of 3 years of experience in a financial services organization or 2 years of experience within a credit rating agency.
• Bachelor's degree required (Finance, Economics, Business, Information Systems, STEM, or related field preferred).
• Experience working with fixed-income products, reference data, entity management, or ratings operations preferred.
• Analytical and problem-solving skills with exceptional attention to detail.
• Ability to interpret information from multiple internal and external sources.
• Ability to work independently while managing multiple priorities in a fast-paced environment.
• Strong written and verbal communication skills.
• Demonstrated commitment to data accuracy and operational excellence.
• Familiarity with Generative AI tools such as ChatGPT for research, data insights, and general productivity is a plus

• Basic to intermediate SQL skills.
• Basic Python knowledge preferred.
• Intermediate proficiency with Microsoft Excel and Word.
• Experience with Jira or similar workflow management tools preferred.
• Experience using AI-powered productivity tools (e.g., ChatGPT, Microsoft Copilot, GitHub Copilot, or similar) to improve research, documentation, data analysis, and operational efficiency preferred.

• Experience supporting credit rating workflows or financial reference data.
• Experience with data governance, metadata, or data quality initiatives.
• Experience working with entity, transaction, and security master data.
• Familiarity with fixed-income securities, structured finance, corporate ratings, or related financial products.

Experience leveraging generative AI tools (e.g., ChatGPT, Microsoft Copilot, Claude, Gemini, or similar) to automate routine tasks, analyze data, create documentation, and identify process improvement

The anticipated annual base salary range for this full-time position is $75,000 to $90,000. Offer amounts are determined by factors such as experience, skills, geography, and other job-related factors.