Data Engineer

• Design, develop, and maintain end-to-end ETL/ELT pipelines using AWS Glue, Redshift, and related AWS services
• Develop and maintain robust data models by understanding business requirements and analytics needs
• Write and optimize complex SQL queries to support reporting, analytics, and downstream data consumers
• Optimize data warehouse schemas, data models, and queries for performance, scalability, and cost efficiency
• Collaborate with data architects, analysts, and business stakeholders to translate business needs into technical data solutions
• Implement data quality, governance, and security best practices across data pipelines
• Automate workflows, monitoring, alerting, and performance tuning in AWS environments
• Manage data ingestion from multiple structured and unstructured data sources
• Troubleshoot and resolve production data issues, ensuring high availability and reliability

• Strong hands-on experience with AWS Redshift, including performance tuning, schema design, and data warehouse optimization
• Expertise in AWS Glue (Glue Studio, Glue Catalog) and PySpark for ETL development
• Solid expertise in data modeling, with the ability to understand business processes and translate them into efficient data models
• Strong proficiency in SQL, with proven ability to write complex, high-performance queries
• Solid understanding of data warehousing concepts, ETL design patterns, and data modeling techniques (Star / Snowflake schemas)
• Experience with AWS services such as S3, Lambda, Athena, Step Functions, and CloudWatch
• Proficiency in Python for data transformation and automation
• Excellent problem-solving, analytical, and communication skills
• 10+ Years of experience
• Qualification: Any Degree

Experience with CI/CD pipelines, Git version control, and Infrastructure as Code (CloudFormation / Terraform) is a plus