About the Company
The company is a leading global financial services provider, delivering large-scale data solutions and distributed platforms to support critical business operations. The organization emphasizes high performance, scalability, and innovation in data engineering, collaborating with diverse teams across the globe.
About the Role
The company is looking for experienced Spark–Scala Developers to join a high-performing data engineering team. The role focuses on designing, developing, and maintaining large-scale distributed data pipelines, working with Spark and Scala, and collaborating in a global Agile environment.
Key Responsibilities
- Design, develop, and maintain scalable Spark-based data processing solutions
- Write clean, efficient, and maintainable Scala code following best practices
- Work in an Agile/Scrum environment, participating in stand-ups, sprint planning, and retrospectives
- Collaborate with global stakeholders and upstream/downstream teams
- Troubleshoot and resolve complex data and performance issues
- Contribute to continuous improvement and adoption of new technologies
Requirements
- 8+ years of hands-on experience with Scala
- Extensive experience with Apache Spark (Spark Core & Spark SQL)
- Proven background in designing and building large-scale distributed data pipelines
- Strong understanding of data structures, ETL concepts, and data warehousing
- Solid experience with SQL and database concepts (SQL/NoSQL)
- Strong analytical and problem-solving skills
- Excellent verbal and written communication skills
- Ability to work effectively in diverse, multi-stakeholder teams and global delivery environments
Nice to Have
- Experience with Spark Streaming
- Knowledge of Hadoop, HDFS
- Familiarity with Hive, Impala, Sqoop
- UNIX/Linux shell scripting experience
Benefits
- Opportunity to work on large-scale, distributed data platforms
- Exposure to cutting-edge data engineering technologies
- Collaborative and high-performing team environment
- Hybrid work model with 3 days onsite in London