Senior Data Specialist

Responsibilities

• Support and enhance data quality, operational efficiency, and data-driven decision-making across Moody’s Analytics
• Develop, execute, and maintain processes to monitor and continuously improve data quality across multiple sources
• Design and contribute to data deduplication and data matching frameworks to improve data integrity
• Analyze existing data operations workflows and identify opportunities for automation and process optimization
• Collaborate with Sales, Content, Product Strategy, and Technology teams to optimize data pipelines and architecture
• Support internal and external stakeholders by responding to data-related requests and providing timely insights

Requirements

• 1–3 years of experience in data operations, data management, data analytics, or automation
• Proficiency in SQL (PostgreSQL, MySQL) for writing and optimizing queries
• Strong Python skills with hands-on experience using Pandas and NumPy
• Understanding of data architectures, data modeling, ETL processes, and data integration
• Experience with Spark or PySpark for distributed data processing
• Experience with data visualization tools such as Power BI, Tableau, or QlikView
• Familiarity with Databricks for collaborative data engineering
• Knowledge of entity resolution, deduplication, and data matching techniques
• Exposure to Generative AI tools or frameworks for data enrichment and automation
• Bachelor’s degree in Computer Science, Data Science, Data Engineering, or a related field

About the Company

Moody's is a global leader in ratings and integrated risk assessment. The Data Estate team, part of the commercial data business within Moody’s Analytics, provides mission-critical data to decision-makers around the globe through flagship products like Orbis. We aim to turn today’s risks into tomorrow’s opportunities by advancing AI and delivering high-quality, accessible insights.