At a Glance
- Tasks: Lead the design and delivery of innovative data solutions in an AI-first environment.
- Company: Join Moody's, a global leader in risk assessment and data engineering.
- Benefits: Inclusive culture, competitive salary, and opportunities for professional growth.
- Other info: Collaborative team focused on delivering high-quality data products and continuous improvement.
- Why this job: Make a real impact by transforming how the world sees risk with cutting-edge technology.
- Qualifications: Experience in data engineering, SQL, Python, and strong stakeholder engagement skills.
The predicted salary is between 70000 - 90000 £ per year.
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- Significant hands-on experience in data engineering, analytics engineering, or related disciplines delivering enterprise data solutions
- Strong proficiency in Databricks, SQL, and Python/PySpark, including building, optimizing, and troubleshooting ETL pipelines
- Experience designing scalable, maintainable data architectures and dimensional models for BI, reporting, and analytical use cases
- Proven ability to partner with business stakeholders to gather requirements, shape solutions, and communicate effectively
- Strong understanding of data engineering best practices including version control, testing, documentation, and governance
- Experience with Git/GitHub for collaborative development, code reviews, and release management
- Exposure to metadata-driven or configuration-based approaches such as YAML-based metric standardization
- Knowledge of Power BI and/or Microsoft Fabric, particularly for semantic modeling and downstream data consumption
- Demonstrated people leadership, including coaching and developing junior engineers
- Strong organizational, problem-solving, and communication skills, with the ability to balance technical delivery and apply AI-enhanced practices to improve productivity
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience
- Lead the design, delivery, and continuous improvement of business-focused data solutions, combining hands-on technical leadership with strong stakeholder engagement in an AI-first environment.
- Partner with business stakeholders to translate reporting, planning, and analytical requirements into scalable data solutions
- Deliver curated, well-documented datasets aligned to agreed definitions and business expectations
- Act as a trusted technical partner, balancing delivery speed, data quality, and long-term scalability
- Architect modular ETL pipelines to improve maintainability, reuse, and traceability
- Define and uphold engineering standards across coding, testing, documentation, and version control practices
- Support BI lakehouse development and integration across the broader data ecosystem
- Manage ETL orchestration, dependencies, and deployments to ensure reliability and operational stability
- Monitor production performance and resolve root causes to prevent recurring data delivery issues
- Apply dimensional modeling and support Unified Star Schema development to ensure semantic consistency
- Mentor and coach junior engineers while promoting strong technical standards and collaborative ways of working
This role sits within MA Business Intelligence, a team focused on delivering high-quality, business-aligned data products that power reporting, analytics, and strategic decision-making. The team operates at the intersection of data engineering and business stakeholders, with a strong emphasis on finance and product strategy use cases. Working within a modern BI Lakehouse environment, the team prioritizes scalable design, semantic consistency, and continuous improvement, while fostering a collaborative culture that embraces innovation and AI-enabled development practices.
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.
Let's begin! Associate Director - Data Engineering in London employer: Moody's Corporation
At Moody's, we pride ourselves on being an exceptional employer that champions inclusivity and innovation. Our collaborative work culture fosters personal and professional growth, offering employees the opportunity to lead in a cutting-edge AI-first environment while developing impactful data solutions. With a commitment to integrity and diverse perspectives, Moody's empowers its team members to thrive and make meaningful contributions to the world of risk assessment.
StudySmarter Expert Advice🤫
We think this is how you could land Let's begin! Associate Director - Data Engineering in London
✨Tip Number 1
Network like a pro! Reach out to current employees at Moody's on LinkedIn or through mutual connections. A friendly chat can give you insider info and might just get your application noticed.
✨Tip Number 2
Prepare for the interview by diving deep into data engineering trends and Moody's projects. Show us that you're not just a candidate, but someone who’s genuinely excited about what we do and how you can contribute.
✨Tip Number 3
Practice your storytelling skills! Be ready to share specific examples of your past work in data engineering. We want to hear how you've tackled challenges and delivered results—make it engaging!
✨Tip Number 4
Don’t hesitate to apply through our website, even if you don’t tick every box. We value diverse perspectives and believe you could be a great fit for this role or others. Just go for it!
We think you need these skills to ace Let's begin! Associate Director - Data Engineering in London
Some tips for your application 🫡
Show Your Passion:When writing your application, let your enthusiasm for data engineering shine through! We want to see how excited you are about the role and how you can contribute to our mission of turning risks into opportunities.
Tailor Your Experience:Make sure to highlight your hands-on experience with Databricks, SQL, and Python/PySpark. We love seeing specific examples of how you've built and optimised ETL pipelines or designed scalable data architectures—this is your chance to show us what you've got!
Communicate Clearly:Effective communication is key! Use your application to demonstrate how you've partnered with business stakeholders in the past. Share how you gathered requirements and shaped solutions, as this will resonate with our values of collaboration and trust.
Don’t Hold Back!:If you’re excited about this opportunity but don’t meet every single requirement, go ahead and apply anyway! We believe that diverse perspectives enrich our team, so don’t hesitate to showcase your unique skills and experiences on our website.
How to prepare for a job interview at Moody's Corporation
✨Know Your Data Engineering Stuff
Make sure you brush up on your data engineering skills, especially in Databricks, SQL, and Python/PySpark. Be ready to discuss your experience with building and optimising ETL pipelines, as well as any challenges you've faced and how you overcame them.
✨Showcase Your Stakeholder Skills
Prepare examples of how you've partnered with business stakeholders in the past. Highlight your ability to gather requirements and translate them into effective data solutions. This role is all about communication, so be ready to demonstrate your collaborative approach.
✨Emphasise Best Practices
Familiarise yourself with data engineering best practices, including version control, testing, and documentation. Be prepared to discuss how you've implemented these in your previous roles, and why they matter for maintaining high-quality data solutions.
✨Be a Mentor at Heart
Since this role involves mentoring junior engineers, think of specific instances where you've coached or developed others. Share your philosophy on leadership and how you promote strong technical standards within a team. This will show that you're not just a tech whiz, but also a great team player.
