Key Responsibilities:

• Work closely with business stakeholders to gather, understand, and translate business requirements into scalable data solutions.
• Design, build, and optimize data pipelines in Azure Databricks using PySpark and SQL.
• Collaborate with analysts and product owners to deliver ad-hoc analyses, as well as end-to-end production-grade data solutions.
• Manage and maintain data lakes, ensuring efficient data ingestion, transformation, and storage.
• Develop data models and datasets optimized for Power BI dashboards and self-service analytics as well as design and create dashboards.
• Participate in CI/CD and DevOps processes for automated deployment and monitoring of data workflows.
• Communicate technical concepts effectively to non-technical business users, providing clarity and actionable insights.

Key Qualifications:

• 3+ years of experience as a Data Engineer. Experience in Azure data ecosystem (Azure Data Factory, Azure Data Lake Gen2, Azure Databricks) is a plus.
• Strong hands-on experience in PySpark, SQL, and Python for data transformation and pipeline automation.
• Experience designing and managing data pipelines and ETL processes using Databricks and Delta Lake.
• Experience in Data Visualization and a good understanding of Power BI data.
• Experience in stakeholder management. Translating business needs into data-driven solutions and presenting findings clearly.
• Familiarity with DevOps concepts, Git, and CI/CD pipelines in Azure DevOps.
• Solid understanding of data governance, data quality, and metadata management principles.

What’s in it for you:

• Competitive salary
• Employees' Provident Fund, medical and other incentives
• Unique working environment where you communicate and work directly with international clients
• Self-development opportunities