At a Glance
- Tasks: Lead data quality remediation and support operations in a dynamic, client-focused environment.
- Company: Join Moody's, a global leader in risk assessment and data solutions.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative team atmosphere with a focus on innovation and ethical AI practices.
- Why this job: Make a real impact by enhancing data quality and driving operational excellence.
- Qualifications: Experience in SQL, Python, and data quality management; strong analytical skills.
The predicted salary is between 60000 - 80000 £ per year.
Deliver high-quality data remediation and operations support, ensuring accurate, timely, and scalable data solutions in a client-facing environment. Act as a primary point of contact for data remediation issues, triaging, prioritising, and resolving critical client-facing data incidents.
Execute remediation activities using SQL and Python to analyse, validate, and improve data quality across multiple datasets. Monitor and enhance data quality by ensuring accuracy, completeness, and consistency through structured processes and controls.
Execute data workflows, pipelines, and integration processes to support efficient and reliable data operations. Identify and implement opportunities for automation and process improvements to enhance operational efficiency.
Coordinate contractor resources, including task allocation, onboarding support, and quality oversight to ensure consistent delivery. Track remediation activities, maintain documentation, and monitor progress against timelines, service levels, and operational targets.
Produce operational reporting on volumes, trends, risks, and performance metrics to support decision-making. Collaborate with cross-functional teams to address root causes, improve remediation playbooks, and align with data strategy objectives.
Escalate complex or high-risk issues with structured insights and recommendations to support timely resolution.
About the Team
Our Data Estate team is responsible for delivering high-quality, trusted commercial data products to clients globally. The team contributes to Moody's by providing comprehensive and reliable data solutions that support critical business decisions, while driving data quality and operational excellence through scalable remediation and governance practices. It also enhances the accessibility and usability of data through efficient processing, integration, and analytics capabilities.
By joining the team, you will be part of a fast-paced, client-focused environment, working on one of the world's leading company data platforms.
Qualifications
- Strong technical expertise in SQL and Python for data analysis, validation, and remediation, enabling accurate and scalable data operations.
- Proven experience in data quality management and remediation processes, ensuring completeness, consistency, and reliability of large datasets.
- Ability to operate in fast-paced, client-facing environments, managing competing priorities and delivering against tight deadlines and service level agreements.
- Experience coordinating cross-functional stakeholders and contractor resources to maintain operational continuity and quality output.
- Knowledge of data processing frameworks, including ETL pipelines, data integration, and data modelling (experience with Databricks or Spark preferred).
- Strong analytical and problem-solving skills with the ability to communicate clearly to both technical and 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.
- Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field.
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.
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.
Client-Facing Data Quality & Remediation Lead in Manchester employer: Moody's Corporation
At Moody's, we pride ourselves on being an exceptional employer, offering a dynamic and inclusive work culture that fosters innovation and collaboration. Our Data Estate team is dedicated to delivering high-quality data solutions in a fast-paced, client-facing environment, providing ample opportunities for professional growth and development. With a commitment to operational excellence and a focus on employee well-being, Moody's empowers its team members to thrive while making a meaningful impact in the world of data.
StudySmarter Expert Advice🤫
We think this is how you could land Client-Facing Data Quality & Remediation Lead in Manchester
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your SQL and Python projects. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common questions related to data quality and remediation. We recommend role-playing with a friend to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Client-Facing Data Quality & Remediation Lead in Manchester
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with SQL, Python, and data quality management. We want to see how your skills align with the role of Client-Facing Data Quality & Remediation Lead!
Showcase Your Problem-Solving Skills:In your application, share examples of how you've tackled data remediation issues in the past. We love seeing candidates who can demonstrate their analytical prowess and ability to communicate solutions effectively.
Highlight Your Teamwork Experience:Since this role involves coordinating with cross-functional teams, be sure to mention any relevant experiences where you’ve collaborated with others. We value teamwork and want to know how you contribute to a positive working environment.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensure you’re considered for this exciting opportunity. We can’t wait to hear from you!
How to prepare for a job interview at Moody's Corporation
✨Know Your SQL and Python Inside Out
Since the role heavily relies on SQL and Python for data analysis and remediation, make sure you brush up on your skills. Prepare to discuss specific projects where you've used these languages to solve data quality issues, and be ready to demonstrate your problem-solving approach.
✨Understand Data Quality Management
Familiarise yourself with data quality management processes. Be prepared to talk about how you've ensured completeness and consistency in large datasets. Think of examples where you've identified and resolved data quality issues, as this will show your practical experience in a client-facing environment.
✨Showcase Your Analytical Skills
This role requires strong analytical and problem-solving skills. During the interview, highlight situations where you've had to analyse complex data sets or troubleshoot data incidents. Use clear examples to illustrate how you communicated findings to both technical and non-technical stakeholders.
✨Demonstrate Your Team Collaboration Experience
Collaboration is key in this role, so be ready to discuss your experience working with cross-functional teams. Share examples of how you've coordinated with different stakeholders and managed contractor resources to maintain operational continuity and quality output.
