Responsibilities

• Design, develop, and maintain scalable ETL / ELT pipelines
• Build and optimize data workflows on Databricks and Azure Cloud
• Develop high-performance SQL transformations and data models
• Work with large-scale structured and semi-structured datasets
• Improve data quality, reliability, and pipeline performance
• Support migration and modernization of enterprise data platforms
• Collaborate with stakeholders to understand business and technical requirements
• Troubleshoot production issues and optimize existing data processes
• Participate in architecture and technical solution discussions
• Mentor junior engineers and share best practices with the team

Qualifications

• At least 5 years of experience in Data Engineering or related roles
• Strong expertise in SQL and ETL development
• Hands-on experience with Azure Cloud and Databricks
• Experience working with enterprise-scale data platforms
• Strong understanding of Data Warehouse and Data Lake concepts
• Experience with PySpark / Spark is highly preferred
• Familiarity with cloud-based data architecture and optimization
• Experience in performance tuning and troubleshooting ETL jobs
• Understanding of CI/CD and version control (Git)
• Good problem-solving and analytical skills
• Able to work independently and communicate effectively with teams