Assistant Director - Data Engineer, Brussels

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 Proven ability to make critical technical design decisions and drive architectural direction for production data systems Demonstrated experience mentoring engineers and fostering technical growth within teams Strong focus on establishing and enforcing engineering best practices including code quality, testing, and documentation standardsEffective communication skills for technical documentation, stakeholder management, and cross‑functional collaboration Strong experience building scalable data applications using Apache Spark, with proficiency in Scala preferred and Python also acceptable Hands‑on experience working with Databricks in a cloud environment (AWS preferred) for large‑scale data processingSolid understanding of distributed computing, data partitioning, and performance optimisation Strong Spark SQL skills for data transformation, modelling, and optimisation Understanding of graph data structures, clustering techniques, and similarity approaches for entity resolution workflows Experience working with modern data formats such as Parquet, Delta Lake, and JSONFamiliarity with statistical methods such as TF‑IDF and similarity metrics in data processing contexts Proficiency with version control and build tools including Git, Gradle, Maven, or SBT Experience with testing frameworks such as ScalaTest or JUnit and test automation practices Ability to leverage AI‑assisted development tools to improve productivity and code qualityStrong analytical and problem‑solving skills in complex data environments

Education Master’s degree in Computer Science, Information Technology, or a related field Equivalent practical experience will also be considered

Responsibilities Design, build, and optimise large‑scale data processing pipelines and graph‑based data solutions, while providing technical guidance and mentoring to support high‑quality engineering delivery.

Lead critical technical design decisions for data pipelines, graph architectures, and system scalability strategies Mentor and develop junior and mid‑level engineers, providing technical coaching and career guidance Conduct architectural code reviews to ensure adherence to engineering best practices and design standardsDefine and enforce testing strategies across the team to maintain code quality and system reliability Design and maintain scalable Spark‑based data pipelines for processing large volumes of data Develop graph‑based analytics including clustering, similarity modelling, and entity resolution approachesImplement parsing, normalisation, and standardisation logic across complex datasets Build and maintain ETL workflows ingesting data from multiple sources such as Delta Lake, Parquet, and S3 Implement data quality frameworks, validation checks, and incremental processing strategies Develop monitoring, diagnostics, and tooling to ensure pipeline reliability and performanceCollaborate with Product, Data Science, and Engineering stakeholders to align technical roadmap with business objectives Document system architecture, data flows, and engineering decisions to support knowledge sharing

About The Team Join our Data Engineering team, responsible for building scalable data pipelines across Change Data Capture, Entity Resolution, and Data Mastering. The team focuses on delivering high‑performance, enterprise‑grade data solutions that support critical business applications. You will work on large‑scale data challenges, contribute to technical innovation, and support the development of engineering capability through mentoring and collaboration.

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.

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