Title: AWS Data Engineer

Responsibilities:

• Design and build scalable data pipelines to ingest, process, and transform structured, semi-structured, and unstructured data from heterogeneous sources.
• Develop batch and streaming pipelines using Amazon Kinesis, AWS Glue, AWS Lambda, and Amazon EMR for real-time and near-real-time processing.
• Implement data models and optimize performance for OLTP and OLAP systems, including Amazon RDS, Amazon Redshift, and DynamoDB.
• Participate in mainframe modernization initiatives by extracting, transforming, and migrating legacy datasets into AWS-native platforms.
• Ensure data quality, lineage, and governance using AWS-native tools like AWS Lake Formation, AWS Glue Data Catalog, and CloudWatch.
• Collaborate with business and application teams to deliver end-to-end data solutions.

Requirements:

• Strong experience with AWS services: Amazon Kinesis, AWS Glue, AWS Lambda, Amazon Redshift, Amazon RDS, DynamoDB, and S3.
• Hands-on experience with Python/Java/Scala for building data pipelines.
• Good knowledge of mainframe data formats (COBOL copybooks, VSAM, DB2) and integration with modern platforms.
• Solid understanding of OLTP vs OLAP workloads and performance optimization best practices.
• Familiarity with DevOps practices and CI/CD pipelines using AWS tools (CodePipeline, CodeBuild, CloudFormation, Terraform).