Moody's Corporation
Senior Software Engineer - Data Engineering

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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
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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


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About The Team
The Digital Content & Innovations Data Engineering team is a collaborative, 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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