Tasks: Develop and implement data processing solutions on Azure, including writing scalable and efficient code for transforming and cleaning large structured and unstructured datasets. Create and maintain data pipelines pulling data from various sources (databases, APIs, streaming platforms). Integrate and transform data to match target formats and models. Design and optimize data storage solutions (data lakes, data warehouses, distributed file systems), focusing on partitioning, compression, and performance. Diagnose performance issues and improve system efficiency through query tuning and caching. Work closely with data scientists, analysts, and business stakeholders to understand requirements and deliver technical solutions. Take full responsibility for solution delivery, ensuring high quality and timely execution. Operate in an Agile environment. Requirements: Experience with Azure cloud infrastructure and Databricks. Strong skills in SQL. Proficiency in Python and PySpark. Excellent communication skills, able to clearly explain technical concepts to team members and stakeholders. Hands-on experience with Agile tools (e.g., JIRA, Azure DevOps). English at B2 level or higher (preferably C1). Nice to have:Knowledge or experience with other cloud platforms, data warehouses, data governance, or business analysis.