Qualifications

• Experience with AWS Glue for data integration and transformation tasks.
• Proficient in PySpark for developing scalable data processing applications.
• Knowledge of Amazon Redshift for managing data warehousing solutions.
• Strong SQL skills for querying and manipulating data effectively.
• Hands-on experience in data pipeline development and cloud data engineering practices.
• Ability to perform data analysis and root cause investigation for quality assurance.
• Demonstrated troubleshooting skills and providing operational support in cloud environments.

Responsibilities

• Manage and maintain Amazon Redshift consumer cluster infrastructure for optimal performance.
• Design and support data pipelines using PySpark and AWS Glue for data processing.
• Monitor and optimize ETL/ELT workflows to ensure timely data delivery.
• Conduct thorough data analysis to resolve quality and operational issues.
• Collaborate with cross-functional teams for data integration and modernization projects.
• Implement best practices in automation and performance tuning for data processes.
• Support production releases and continuously improve AWS-based data platforms.

Benefits

• Opportunity to work with cutting-edge cloud technologies.
• Collaborative work environment with diverse teams.
• Focus on innovation and continuous improvement.
• Access to professional development resources and training.
• Impactful role in enhancing data reporting capabilities.