Data Engineer (Scala / Spark / Azure)

Technologies we use

About the project

Your responsibilities

• Implement new data structures by adding tables and columns based on provided specifications
• Maintain and troubleshoot existing pipelines, including identifying and fixing bugs
• Modify and enhance data transformations in response to evolving business requirements
• Optimize data processing workflows to improve performance and efficiency
• Collaborate with other team members to ensure data consistency and quality
• Use Databricks notebooks for debugging, testing, and validating data processing logic

Our requirements

• Hands-on experience with Scala (at least one commercial or substantial project; expert level not required)
• Experience working with Apache Spark
• Familiarity with Databricks for data processing and development
• Experience with Azure Data Factory (ADF) or similar orchestration tools
• Understanding of data pipeline concepts, ETL/ELT processes, and data modeling basics
• Proactive and communicative approach to work
• Good command of English (written and spoken) is required
• Ability to work with existing codebases and adapt to changing requirements

Optional

• Experience with Azure ecosystem components
• Exposure to performance tuning in Spark
• Familiarity with CI/CD practices in data engineering

This is how we work on a project

Development opportunities we offer

What we offer

• Opportunity to work on scalable data processing systems in a cloud environment
• Collaborative team focused on practical problem-solving and continuous improvement
• Exposure to modern data engineering tools and architecture

Benefits