Data Engineer

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for processing large volumes of data
• Build and optimize data models, data warehouses, and data lake solutions
• Develop robust data integration workflows using AWS Glue and orchestration tools such as Apache Airflow
• Manage and optimize Snowflake environments, including performance tuning, query optimization, and cost management
• Write efficient and scalable SQL queries and Python scripts for data transformation and automation
• Implement CI/CD practices and deployment automation using Azure DevOps
• Collaborate with cross-functional teams including Data Analysts, Data Scientists, and Product Managers
• Ensure data quality, governance, security, and compliance across data platforms
• Troubleshoot and resolve data pipeline and performance-related issues

Requirements

• 5+ years of experience in Data Engineering or related roles
• Strong proficiency in SQL and Python
• Hands-on experience with Snowflake Data Warehouse architecture and performance optimization
• Proven experience with AWS Glue for data integration and transformation
• Experience with workflow orchestration tools such as Apache Airflow
• Strong understanding of data modeling, data warehousing, and data lake concepts
• Experience with Azure DevOps, including version control and CI/CD pipelines
• Experience working in Agile/Scrum environments

Preferred Qualifications

• Experience with large-scale data migration and modernization projects
• Exposure to AWS cloud services and ecosystem
• Knowledge of data governance and security best practices
• Relevant cloud or Snowflake certifications