Senior Data Specialist

At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence. If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.  Skills and Competencies 5-8 experience reviewing, correcting, enriching, and validating entity data to improve accuracy, completeness, and consistency across systems Strong understanding of data quality, data governance, remediation protocols, documentation standards, and audit support requirements Ability to identify recurring data issues, recognize patterns, and translate insights into practical recommendations for process improvement Proficiency with Excel and familiarity with Jira, Databricks, SQL, Python, or PySpark is advantageous Interest in using Gen AI tools, including MS Copilot and OpenAI, to support data collection, remediation, automation, and process improvement opportunities Strong communication and collaboration skills, with the ability to work effectively with data operations teams, product managers, developers, sales teams, and other stakeholders Education Bachelor’s degree in Data Management, Computer Science, Information Systems, Business, Finance, Economics, or a related discipline preferred Relevant certification or training in data quality, data governance, analytics, SQL, Python, Databricks, or automation tools would be an advantage Responsibilities Review, correct, enrich, and validate entity data across systems by resolving inaccuracies, duplicates, and missing information, while documenting updates, justifications, and observations throughout the remediation process Identify recurring data quality issues, patterns, and inconsistencies, and share actionable insights with team leads or data quality managers to strengthen remediation checklists, quality standards, and process improvements Follow established data governance, quality, and audit protocols by maintaining accurate documentation, supporting audit evidence requests, and participating in peer reviews or quality checks to uphold consistent data standards Coordinate operational workflows by creating and managing centralized Jira tickets, handling and following up on Salesforce client cases, prioritizing remediation tasks, and supporting reports or dashboards that summarize remediation outcomes and data improvements Collaborate with data operations colleagues and cross-functional stakeholders, including Product Managers, Developers, Information Providers, and Sales teams, while communicating progress, data challenges, recurring issues, and team meeting notes clearly and professionally Support continuous improvement and deputy management activities by exploring Python, PySpark, Databricks, MS Copilot, and OpenAI-enabled automation opportunities, preparing technical proposals, assisting with team output monitoring, coaching, training, ad hoc project distribution, leave cover, and data source change implementation About the team The Contacts team is responsible for maintaining the quality, accuracy, and completeness of people and professional profile data used across Moody's products and solutions. The team works closely with