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Senior Software Engineer - Data Engineering

Moody's -
Manchester

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Job details

Qualifications

Data development experience
Data integration
Stakeholder collaboration
Data and database experience
Master's degree
Databases
ETL data integration
Bachelor's degree
Machine learning
Mentoring
GitHub
Agile
Apache
AI
Communication skills

Full job description

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

3+ years of experience within a data engineering or software development team
Hands-on experience designing and developing data integration/ETL pipelines from diverse data sources and formats
Hands-on experience with Apache Airflow, dbt, and Python
Strong database skills with Postgres SQL, DynamoDB, Snowflake, and Databricks
Experience collaborating with Agile teams, product owners, and cross-functional stakeholders, with strong communication skills for both technical and non-technical audiences
Experience applying AI-assisted development tools (e.g., GitHub Copilot, generative AI coding assistants) to improve engineering productivity, code quality, and delivery efficiency
Understanding of data engineering considerations for AI and machine learning workloads, including data quality, governance, lineage, and scalability requirements

Education

Bachelor’s degree or equivalent experience; Master’s degree is a plus

Responsibilities

In this role, you will design, build, and support highly scalable data engineering solutions that power Moody’s next‑generation digital content platform

Design, develop, and maintain scalable data pipelines using DataBricks, Snowflake, Apache Airflow, dbt (SQL), and Python within AWS
Support platform optimization, infrastructure improvements, process control enhancements, and system upgrades
Collaborate with Moody’s technical teams and business partners throughout design and implementation phases
Engage cross-functional teams to understand data requirements and deliver scalable solutions
Educate and mentor others through code reviews, documentation, and workshops

About the Team

The Digital Content & Innovations Data Engineering team is a collaborative, AI-focused, forward‑thinking group focused on building highly available, cloud‑native data solutions that power Moody’s digital content ecosystem. The team partners closely with multiple engineering and product teams to drive modernization, implement scalable architectures, and deliver innovative solutions that enable reliable, high‑quality content experiences for users

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.

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