Aws Developer

• Primary skills:Technology->Data On Cloud - NoSQL->Amazon Dynamo DB,Technology->Data On Cloud - Platform->AWS

Responsibilities

• Design, develop, and maintain ETL/ELT pipelines using AWS Glue.
• Develop AWS Glue jobs using PySpark, and SQL for large-scale data processing.
• Build data ingestion and transformation pipelines across structured and semi-structured data sources.
• Configure and manage AWS Glue Data Catalog, Jobs, Workflows, and Triggers.
• Work with AWS services such as Amazon S3, Redshift, and IAM.
• Implement data transformations, validations, data-quality checks, and reconciliation processes.
• Optimize Glue/Spark jobs for performance, scalability, reliability, and cost efficiency.
• Implement incremental loads, partitioning strategies, error handling, restart/recovery, and audit frameworks.
• Troubleshoot ETL pipeline failures and production performance issues.
• Implement appropriate security controls including IAM roles, encryption, and access management.
• Support migration of legacy/mainframe or on-premises ETL workloads to the AWS cloud data platform.
• Develop automated deployment processes using CI/CD and Infrastructure-as-Code practices where applicable.
• Collaborate with data architects, analysts, business teams, and cloud/platform teams to translate requirements into scalable data solutions.
• Prepare technical design documents, mapping specifications, operational documentation, and deployment/runbook documentation.
• 2 years of overall Data Engineering / ETL development experience.
• Strong hands-on experience developing production-grade AWS Glue,Python and PySpark solutions.
• Experience handling high-volume datasets and complex transformations in AWS environments. Preferred Certification
• AWS Certified Data Engineer – Associate or other relevant AWS certification