Senior Scala Data Engineer – Distributed Data Systems

The role is based in the financial sector, focusing on advanced data transformation and enrichment workflows within a modern data platform that supports analytics, machine learning, and intelligent automation at scale.

• 5+ years of hands-on experience with Spark and Scala, some exposure to Python
• Experience with the Hadoop ecosystem including Hive, HDFS, Oozie, MapReduce
• Strong command of SQL dialects used in Spark or Hive
• Proven ability to build, deploy, and manage data flows in large-scale systems
• Practical experience with Git/Bitbucket and collaborative workflows
• Strong English communication skills (spoken and written)

Nice to have:

• Familiarity with version control branching strategies and CI/CD pipelines
• Experience with Agile/SAFe project delivery models
• Exposure to AWS (certification a plus)
• Hands-on use of IBM Cloud Pak for Data
• Interest or experience with machine learning workflows

• Design and maintain robust ETL/ELT pipelines using Apache Spark and Scala
• Develop distributed data processing systems for large volumes of structured and unstructured data
• Collaborate with data scientists to prepare and deliver clean datasets for machine learning and analytics
• Support real-time and batch data workflows across modern data infrastructure
• Participate in sprint reviews and team demos to present technical progress
• Maintain codebases via Git and contribute to high-quality, testable code