Requirements:
- Experience with Azure Databricks, including notebook development, job orchestration, cluster management, and Delta Lake
- Good knowledge of Azure data services such as Data Factory, Data Lake Storage Gen2, Azure SQL, and Key Vault
- Strong SQL and PySpark skills for processing and transforming large data volumes
- Understanding of Data Warehousing, Business Intelligence, and physical data modeling concepts
- Experience with database implementation and performance optimization
- Ability to build and maintain scalable data pipelines and workflows
- Experience translating business requirements into technical data solutions
- Knowledge of testing, debugging, documenting, and supporting data applications and processes
- Ability to work independently and in cross-functional international environments
Responsibilities:
- Develop and support scalable data pipelines using Azure Databricks and Azure data services
- Process and transform large datasets with PySpark and SQL across batch and streaming environments
- Maintain backend data flows, transformation logic, and reporting-related processes
- Collaborate with analysts and technical stakeholders to deliver reliable data solutions
- Contribute to technical analysis, project planning, and implementation activities
- Perform ad-hoc data analysis involving complex datasets and business requirements
- Handle testing, troubleshooting, documentation, and support activities for data processing solutions
- Improve and maintain existing applications, workflows, and pipeline components
- Support ongoing data engineering initiatives within telecommunications and business intelligence environments