Description

You will lead the development and maintenance of data processing infrastructure on AWS.

Responsibilities

• Develop data processing pipelines using AWS Glue and EMR.
• Implement Iceberg-based data lake solutions following data lake best practices.
• Develop efficient ETL workflows using PySpark.
• Orchestrate data workflows using AWS Step Functions.
• Automate data tasks and manage logging/monitoring using Python and CloudWatch.

Required Skills

• 8+ years of experience in data engineering with strong AWS Cloud expertise.
• Hands-on experience with AWS Glue and AWS EMR for data processing.
• Proven experience building ETL workflows using PySpark.
• Knowledge of data lake architecture and Iceberg implementations.
• Experience using AWS Step Functions for workflow orchestration.
• Understanding of DynamoDB concepts, including GSIs.
• Proficiency in Python scripting for automation.
• Experience with AWS monitoring and logging tools (CloudWatch).
• Bachelor's degree in Computer Science or related field.

Key Skills

Education

Any Graduate