Description

You will design, develop, test, deploy, and maintain large-scale data pipelines on AWS. You own the full lifecycle of data ETL, integration, and automation work.

This role is on-site.

Responsibilities

• Develop and maintain data pipelines using native AWS services, including AWS Glue and AWS Data Migration Service.
• Deliver high-quality ETL solutions by gathering and implementing technical requirements from cross-functional teams.
• Implement CI/CD processes using Jenkins, including writing testing scripts and automating workflows.
• Own data ETL, pipeline, integration, and automation work within the AWS environment.

Required Skills

• 5+ years of experience in data engineering specifically on the AWS platform.
• Proficiency in Spark, PySpark, Python, and SQL.
• Experience with AWS data stores: S3, RDS, DynamoDB, Redshift, and AWS Data Lake.
• Knowledge of AWS services: Glue, Lambda, Athena, EC2, SQS, and SNS.
• Proficiency in CI/CD practices and familiarity with Jenkins.
• Experience with Infrastructure as Code using Terraform or CloudFormation.
• Familiarity with Git and working within an Agile/Scrum team structure.
• Basic understanding of AWS networking components (VPC, SG, Subnets).

Key Skills

Education

Any Graduate