Data Engineer

PassFort; Brussel Hoofdstad; Sur place; EUR 50 000 - 70 000; Plein temps

Résumé du poste

PassFort is looking for a Data Engineer to develop scalable data pipelines and ETL workflows, primarily using Apache Spark and Databricks in a cloud environment. You will be part of a team that works on large-scale data challenges, collaborating with cross-functional teams to deliver high-quality data solutions.

A Bachelor's or Master's in Computer Science or a related field is required, along with practical experience in building data applications.

Qualifications

• Experience building scalable data applications using Apache Spark.
• Hands-on experience with Databricks in a cloud environment.
• Good understanding of distributed computing and performance optimisation.

Responsabilités

• Support the design and development of Spark-based data pipelines.
• Build and maintain ETL workflows ingesting data from Delta Lake and S3.
• Document data flows and technical solutions.

Connaissances

Scalable data applications using Apache Spark

Databricks in AWS

SQL for data transformation

Graph data structures

Version control with Git

Analytical skills

Communication skills

Formation

Bachelor’s or Master’s degree in Computer Science or Information Technology

Outils

Apache Spark

Databricks

Git

Description du poste

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.

Skills And Competencies

• 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)
• Good understanding of distributed computing, data partitioning, and performance optimisation
• Experience working with modern data formats such as Parquet, Delta Lake, and JSON
• Strong SQL skills for data transformation and querying
• Understanding of graph data structures, clustering techniques, and similarity approaches
• Familiarity with statistical methods such as TF-IDF and similarity metrics
• Proficiency with version control and build tools including Git, Gradle, Maven, or SBT
• Awareness of code quality, maintainability, and testing practices using frameworks such as ScalaTest or JUnit
• Experience contributing to testing approaches including unit and integration testing
• Ability to use AI-assisted development tools to improve productivity and support development tasks
• Strong analytical and problem-solving skills
• Effective communication skills and ability to collaborate within cross‑functional teams
• Willingness to learn new technologies and develop engineering expertise

Education

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

Responsibilities

• Support the design and development of Spark-based data pipelines for processing large volumes of data
• Implement parsing, normalisation, and standardisation logic across datasets
• Assist in developing graph-based analytics and entity resolution workflows
• Build and maintain ETL workflows ingesting data from sources such as Delta Lake, Parquet, and S3
• Contribute to data quality checks, validation, and incremental processing approaches
• Write and maintain unit and integration tests to support reliability
• Support monitoring and troubleshooting of data pipelines
• Collaborate with cross-functional teams including Product, Data Science, and Engineering
• Document data flows and technical solutions
• Participate in code reviews and contribute to engineering best practices

About The Team

Join our Data Engineering team, responsible for building scalable data pipelines across Change Data Capture, Entity Resolution, and Data Mastering. You will work on large-scale data challenges in a collaborative environment, contributing to high-quality data solutions and developing your technical capabilities.

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.