Data Engineer (Azure / Databricks / Spark)

Join a modern data engineering team focused on delivering scalable, cloud-native data solutions using Azure, Databricks, and Spark. The team environment is agile, collaborative, and quality-driven, emphasizing CI/CD, testing, and performance optimization.

• Hands-on experience with Azure Databricks
• Experience with Azure services such as Data Factory
• Proficient in Python programming
• Solid understanding of Spark, including Spark SQL and performance optimization
• Experience with automated unit testing and code quality best practices
• Working knowledge of CI/CD pipelines (such as Azure DevOps)
• Familiarity with SDLC and agile methodologies
• English proficiency at B2 level

Nice to have:

• Experience with Snowflake
• Knowledge of dbt, Airflow, or Data Mesh architecture
• Background in regulated industries such as pharma or finance

• Design, develop, and maintain robust ETL/ELT data pipelines using Azure Databricks and Spark
• Optimize data transformation workflows for performance and cost-efficiency
• Build and deploy data pipelines through CI/CD workflows using Azure DevOps (or similar)
• Work closely with analysts, data scientists, and product teams to deliver clean, reliable data
• Implement and monitor automated unit tests ensuring code quality and maintainability
• Contribute to team standards through code reviews and knowledge sharing
• Follow SDLC principles in agile team setups