Description

You will design and implement data processing workflows within an AWS environment, owning the full lifecycle from ETL pipelines to data warehousing.

This role is on-site.

Responsibilities

• Build and maintain ETL pipelines using AWS Glue and PySpark.
• Manage data warehousing tasks and performance within Amazon Redshift.
• Develop and orchestrate complex data workflows using Oozie and Hive.
• Provision and manage cloud infrastructure through AWS CloudFormation.
• Optimize data storage and retrieval using Amazon EMR and DynamoDB.

Required Skills

• 5+ years of professional experience in data engineering.
• Expert-level proficiency in Python and PySpark.
• Hands-on experience building ETL pipelines with AWS Glue.
• Experience managing and tuning Amazon Redshift clusters.
• Proficiency with Hive and Oozie for workflow orchestration.
• Experience using AWS CloudFormation for infrastructure as code.
• Working knowledge of Amazon EMR and DynamoDB.
• Bachelor's degree or equivalent professional experience.

Key Skills

Education

Any Graduate