AWS Data Engineer

About the role

Client is seeking an experienced AWS Data Engineer to design, build, and support scalable cloud-based data pipelines. The ideal candidate will have strong hands-on experience with Python, PySpark, ETL development, and AWS data services. This person will work with engineering, analytics, and business teams to process large datasets and deliver reliable, production-ready data solutions.

Responsibilities

• Design, develop, and maintain scalable ETL and data-processing pipelines
• Build data-engineering solutions using Python and PySpark
• Process and transform large structured and unstructured datasets
• Develop cloud-based data solutions using AWS services
• Monitor data pipelines and troubleshoot data-quality and performance issues
• Optimize ETL workflows for reliability, scalability, and efficiency
• Partner with application, analytics, and business teams to understand data requirements
• Perform unit testing, code reviews, deployments, and production support
• Follow data security, governance, and engineering best practices
• Document technical designs, workflows, and operational procedures

Required Qualifications

• Minimum 7 years of data engineering experience
• Strong hands-on experience with Python, PySpark, ETL, and AWS
• Strong SQL and data-transformation skills
• Experience processing large datasets in distributed environments
• Understanding of data modeling and cloud-based data-pipeline architecture
• Experience troubleshooting and supporting production data pipelines
• Strong communication and problem-solving skills

Preferred Qualifications

• Hands-on Databricks experience
• Experience with cloud-based data lakes and distributed data-processing platforms