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 an inclusive employer.
- Benefits: Competitive salary, diverse workplace, and opportunities for professional growth.
- Other info: Collaborative team culture focused on innovation 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, strong skills in SQL, Python, and ETL pipeline management.
The predicted salary is between 80000 - 100000 £ per year.
This job is with Moody's, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We strive 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
Education
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience
Responsibilities
- 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
About the Team
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.
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.
Associate Director - Data Engineering employer: Moody's
At Moody's, we pride ourselves on being an inclusive employer that champions diverse perspectives and fosters a collaborative work culture. Our commitment to employee growth is evident through mentorship opportunities and a focus on continuous improvement in a cutting-edge AI-first environment. Located in a vibrant community, we offer our team members the chance to engage with innovative data solutions while making a meaningful impact in the world of risk assessment.
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We think you need these skills to ace Associate Director - Data Engineering
Some tips for your application 🫡
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✨Brush Up on Your Statistics
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
