Moody’s is Hiring for Data Management Associate

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Job Overview

Moody’s is seeking a Data Management Associate to join its Data Estate division in Gurugram, Haryana. The role involves managing and improving structured finance data processes, including extraction, transformation, and quality assurance. The ideal candidate should have strong analytical, coding, and problem-solving skills, along with a basic understanding of securitization structures (ABS, RMBS, CMBS). This is an excellent opportunity to work at the intersection of finance, data, and technology in a globally respected organization.

Job Details

Company: Moody’s Corporation
Job Position: Data Management Associate
Location: Gurugram, Haryana, India
Experience: 0–2 years
Qualification: Bachelor’s degree in Finance, Economics, Engineering, Computing, Statistics, or Mathematics (CFA/FRM/SQL/Python certifications preferred)
Salary: ₹8–12 LPA (estimated based on role and location)

Key Responsibilities

  1. Maintain and manage data extraction, transformation, and quality assurance processes.
  2. Troubleshoot and resolve extraction delays and data management issues.
  3. Collaborate with cross-functional teams including engineers, vendors, and financial analysts.
  4. Identify and acquire data from periodic reports and securitization deals.
  5. Support data-related queries from client-facing and internal teams.
  6. Develop, enhance, and automate ETL tools and workflows.
  7. Contribute to deal structure setup for EMEA and Australian securitization transactions.
  8. Perform data quality checks and ensure timely resolution of discrepancies.
  9. Utilize coding skills (Python, SQL, VBA, or C#) to query, analyze, and visualize data.
  10. Participate in product development and software enhancement discussions.
  11. Support internal stakeholders in analyzing new securitization products.
  12. Document processes and contribute to internal knowledge sharing.
  13. Create and test specifications for productivity improvement projects using Jira or similar tools.
  14. Communicate effectively with trustees, issuers, and arrangers to resolve data issues.
  15. Actively contribute to team development, training, and process improvements.
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Required Skills and Knowledge

  1. Strong quantitative, analytical, and problem-solving skills.
  2. Good communication and teamwork abilities.
  3. Basic understanding of structured finance (RMBS, ABS, CMBS).
  4. Hands-on experience with SQL, Python, VBA, or similar scripting languages.
  5. Ability to work independently while collaborating effectively with global teams.
  6. Familiarity with ETL processes and data visualization.
  7. Attention to detail and strong organizational skills.
  8. Knowledge of data quality frameworks and QA methodologies.
  9. Familiarity with project tracking tools (e.g., Jira).
  10. Passion for learning and adapting to new technologies.
  11. Exposure to finance and data-driven environments.
  12. Capability to handle large datasets efficiently.
  13. Good understanding of data governance and workflow automation.
  14. Strong documentation and process management skills.
  15. Self-motivated attitude with a focus on timely delivery and accuracy.

About Moody’s

Moody’s Corporation is a global leader in integrated risk assessment and credit ratings, helping businesses make informed decisions through advanced analytics and data-driven insights. With operations in over 40 countries, Moody’s drives innovation in financial intelligence, harnessing AI and data science to transform how the world perceives and manages risk.

Why Join Moody’s

  1. Opportunity to work with global leaders in financial analytics and risk assessment.
  2. Exposure to advanced data management and AI-driven technologies.
  3. Collaborative, inclusive, and innovation-focused culture.
  4. Comprehensive training and development programs.
  5. Competitive compensation and career growth opportunities.
  6. Diverse and global work environment.
  7. Work on high-impact projects across structured finance domains.
  8. Strong emphasis on ethics, trust, and data integrity.
  9. Access to cutting-edge tools and proprietary systems.
  10. Opportunities for cross-departmental collaboration and upskilling.
  11. Support for professional certifications like CFA, FRM, or Python.
  12. Hybrid work flexibility.
  13. Commitment to diversity, equity, and inclusion.
  14. Mentorship and peer learning opportunities.
  15. Work for a company shaping the future of financial intelligence.
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