Data Engineer

About the role

Moody's is looking for a Data Engineer to design, develop, and optimise data pipelines and processing solutions in a scalable, cloud‑based environment. You will work with cutting‑edge technologies to transform risk data into actionable insights for our global clients.

Key responsibilities

• Support the design, development, and optimisation of data pipelines using Apache Spark and Databricks.
• Implement data transformation and querying logic with strong SQL skills.
• Handle modern data formats such as Parquet, Delta Lake, and JSON.
• Apply distributed computing concepts, data partitioning, and performance tuning.
• Collaborate with cross‑functional teams to deliver reliable, maintainable code.

Required profile

• 3‑5 years of experience building scalable data applications.
• Bachelor’s or Master’s degree in Computer Science, IT or related field (or equivalent experience).
• Strong analytical and problem‑solving abilities.
• Effective communication and teamwork skills.
• Curiosity about AI tools and responsible AI practices.

Required skills

• Apache Spark (Scala preferred, Python acceptable)
• Databricks on AWS
• SQL
• Distributed computing concepts and performance optimisation
• Parquet, Delta Lake, JSON
• Graph data structures, clustering, similarity metrics (e.g., TF‑IDF)
• Version control (Git) and build tools (Gradle, Maven, SBT)
• Testing frameworks (ScalaTest, JUnit)
• AI‑assisted development tools

What we offer

• Opportunity to work on AI‑driven risk analytics at a global leader.
• Collaborative, inclusive environment that encourages innovation.
• Continuous learning and professional development.