About the Company
The company’s Open Data & AI Business Unit delivers data and artificial intelligence projects for large enterprise clients. Its teams work in hybrid, agile, and collaborative environments on complex digital transformation initiatives.
About the Role
The company is seeking a Data Engineer with Scala, Spark, and Snowflake expertise to design and develop reliable data pipelines.
The engineer will contribute to the migration of Spark and Scala workloads from Hadoop to Snowflake and help introduce development best practices across the RPBI, RBS, and DMP feature teams.
Responsibilities
- Develop and maintain robust, high-performance data pipelines using Snowflake and Snowpark.
- Contribute to the migration of Spark and Scala processing workloads from Hadoop to Snowflake.
- Apply and promote development best practices related to code quality, testing, performance, and clean code.
- Contribute to the design of data flows, data models, and transformations.
- Ensure the quality, consistency, and maintainability of delivered data processes.
- Maintain reliable, production-ready CI/CD pipelines.
- Produce software and technical documentation.
- Work within an Agile Scrum environment.
Requirements
- Expertise in Scala and Spark.
- Experience working with Snowflake and Snowpark.
- Knowledge of the Hadoop and Cloudera ecosystem.
- Experience migrating Hadoop-based Spark and Scala workloads to Snowflake.
- Understanding of data pipeline design, data modelling, and transformation processes.
- Knowledge of software quality, testing, performance optimisation, and clean-code practices.
- Experience with CI/CD pipelines.
- Proficiency with Git.
- Experience working in an Agile Scrum environment.
Recruitment Process
- A brief telephone conversation.
- An approximately one-hour interview with the HR team to discuss the candidate’s experience, professional goals, and the position.
- An interview with the future manager.
- A final technical interview with one of the company’s experts.