Description

You will own the development and maintenance of data processing systems on AWS.

Responsibilities

• Build and maintain ETL pipelines using Python and PySpark on AWS Glue and other compute platforms.
• Orchestrate workflows using AWS Step Functions and serverless components like Lambda.
• Implement messaging and event-driven patterns utilizing AWS SNS and SQS.
• Design and optimize data storage and querying within Amazon Redshift.
• Ensure data quality, monitoring, error handling, and provide operational support for pipelines.

Required Skills

• 5+ years of professional experience in relevant roles.
• Strong proficiency in Python and PySpark for large-scale data processing.
• Proven hands-on experience with AWS services: Lambda, SNS, SQS, Glue, Redshift, Step Functions.
• Solid SQL skills, including data modeling and query optimization.
• Experience implementing ETL best practices, data quality checks, and monitoring/alerting.
• Familiarity with version control using Git.
• Understanding of basic DevOps and CI/CD workflows.
• Experience with ETL Pipelines.

Key Skills

Education

Any Gradute