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Senior Data Specialist

Greater Manchester, England

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Apply at Moody's

What you’ll work on

Full posting
  • Support and enhance data quality and operations across multiple sources, ensuring reliable, scalable, and efficient data delivery.

  • Develop and execute processes to monitor, manage, and improve data quality across datasets

  • Design and implement data deduplication frameworks to improve data accuracy and usability

From the employer’s posting
Responsibilities Support and enhance data quality and operations across multiple sources, ensuring reliable, scalable, and efficient data delivery. Develop and execute processes to monitor, manage, and improve data quality across datasets
Support and enhance data quality and operations across multiple sources, ensuring reliable, scalable, and efficient data delivery. Develop and execute processes to monitor, manage, and improve data quality across datasets Design and implement data deduplication frameworks to improve data accuracy and usability
Develop and execute processes to monitor, manage, and improve data quality across datasets Design and implement data deduplication frameworks to improve data accuracy and usability Analyze and optimize data operations workflows, identifying automation opportunities to increase efficiency

What you’ll bring

All qualifications

Core experience

  • Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field
Qualification wording
Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field

Tools in this posting

  • Python
  • SQL
  • Databricks
  • MySQL
  • PostgreSQL
  • Snowflake
  • Spark
  • NumPy
  • pandas
  • SQL Server
Source — Tool mentions in context
- Strong SQL proficiency (e.g., PostgreSQL, MySQL, SQL Server) to extract, transform, and optimize data for reporting and operational use - Hands-on Python experience (Pandas, NumPy) for data manipulation and analysis, supporting scalable data workflows - Understanding of data architecture, data modeling, and ETL processes to ensure efficient data integration and pipeline development
- 1–3 years’ experience in data operations, data management, analytics, or automation, enabling effective handling and transformation of large datasets - Strong SQL proficiency (e.g., PostgreSQL, MySQL, SQL Server) to extract, transform, and optimize data for reporting and operational use - Hands-on Python experience (Pandas, NumPy) for data manipulation and analysis, supporting scalable data workflows
- Strong communication and problem-solving skills to collaborate across global teams and translate complex data insights into actionable outputs - Familiarity with data platforms such as Databricks, Spark, Snowflake, or similar technologies - Ability to communicate technical concepts clearly to non‑technical stakeholders

Job description

View original posting ↗

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

  • 1–3 years’ experience in data operations, data management, analytics, or automation, enabling effective handling and transformation of large datasets
  • Strong SQL proficiency (e.g., PostgreSQL, MySQL, SQL Server) to extract, transform, and optimize data for reporting and operational use
  • Hands-on Python experience (Pandas, NumPy) for data manipulation and analysis, supporting scalable data workflows
  • Understanding of data architecture, data modeling, and ETL processes to ensure efficient data integration and pipeline development
  • Experience implementing data quality frameworks to ensure accuracy, consistency, and completeness of datasets
  • Strong communication and problem-solving skills to collaborate across global teams and translate complex data insights into actionable outputs
  • Familiarity with data platforms such as Databricks, Spark, Snowflake, or similar technologies
  • Ability to communicate technical concepts clearly to non‑technical stakeholders
  • Basic understanding of artificial intelligence concepts, with curiosity and enthusiasm for learning how AI tools can be used to improve processes and drive efficiency
  • Interest in exploring AI systems and a willingness to develop awareness of responsible AI practices, including risk management and ethical use

Education

  • Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field

Responsibilities

Support and enhance data quality and operations across multiple sources, ensuring reliable, scalable, and efficient data delivery.

  • Develop and execute processes to monitor, manage, and improve data quality across datasets
  • Design and implement data deduplication frameworks to improve data accuracy and usability
  • Analyze and optimize data operations workflows, identifying automation opportunities to increase efficiency
  • Collaborate with cross-functional teams (Sales, Product, Technology) to align data solutions with business needs
  • Support stakeholders by delivering data insights and responding to data-related queries
  • Contribute to the development and enhancement of enterprise data platforms, ensuring integrity and scalability
  • Maintain best practices in data governance, data modeling, and pipeline optimization

About the Team

Our Data Estate team is responsible for delivering high-quality, mission-critical data that powers decision-making across global markets. We provide comprehensive company data through flagship platforms such as Orbis, we enable clients to access, analyze, and act on complex datasets efficiently, and we drive continuous improvements in data quality, accessibility, and operational excellence. By joining our team, you will contribute to innovative data solutions supporting global customers across industries.


Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.

Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

Complete your application on careers.moodys.com. The employer’s form will show what is required.

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Source & posting history

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Location & working pattern

Greater Manchester, England

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Status in our records
Active
First seen by us
Sep 5, 2026
Recorded sightings
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Last seen by us
Sep 30, 2026

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