Description

Build and maintain data processing pipelines in an AWS environment.

Responsibilities

• Develop data processing logic using Python and PySpark.
• Manage and optimize data workflows using AWS Glue and EMR.
• Implement serverless data tasks using AWS Lambda.
• Maintain and query large-scale datasets in Redshift and S3.

Required Skills

• 10+ years of professional software or data engineering experience.
• 5+ years of direct experience working with AWS services.
• Proficiency in Python.
• Experience with PySpark for distributed data processing.
• Hands-on experience with AWS Glue.
• Hands-on experience with Amazon Redshift.
• Hands-on experience with Amazon EMR.
• Hands-on experience with AWS Lambda.
• Hands-on experience with Amazon S3.

Preferred Skills

• Experience with other AWS data services beyond the core stack.

Key Skills

Education

Any Graduate