Azure Data Engineer (ID:3410)

• Design, develop, and maintain scalable ETL/ELT data pipelines using Azure Databricks, Python, and PySpark
• Build, optimize, and manage analytical data models to support reporting, analytics, and downstream applications
• Collaborate closely with data engineers, product owners, business analysts, and stakeholders to gather and translate business requirements into technical solutions
• Publish clean, well-structured, and optimized datasets for Power BI dashboards and reports
• Manage and optimize data storage solutions, including Delta Lake, data lakes, and data warehouses
• Troubleshoot pipeline failures and data issues to ensure accuracy, consistency, and completeness
• Document data flows, architectures, and operational processes
• Support CI/CD practices for data pipelines using Git and DevOps tools

• 6-8 years of overall experience as a Data Engineer or in a similar data-focused role
• Strong hands-on experience with Microsoft Azure, particularly Azure Databricks and Azure Data Factory
• Advanced proficiency in Python and PySpark for large-scale data processing
• Solid expertise in Delta Lake, cluster management, and Databricks notebook development
• Strong knowledge of data modelling concepts (star schema, snowflake schema, semantic models)
• Proven experience building or supporting Power BI datasets, data models, and optimized data feeds
• Strong SQL skills for complex querying and data transformation
• Familiarity with CI/CD practices for data engineering workflows

You should possess the ability to:

• Translate complex business requirements into scalable technical data solutions
• Work effectively in cross-functional and agile teams
• Analyze data issues and resolve them with a strong problem-solving mindset