Senior Data Engineer

• Strong hands-on experience in Python programming and backend data engineering development.

• Expertise in PySpark and Python-based data processing frameworks for handling large-scale data pipelines.

• Experience working with AWS Glue and PySpark for ETL development and data transformation processes.

• Good working knowledge of Python libraries such as Pandas, NumPy, and Joblib.

• Experience in parallel batch processing using Python for optimized performance and scalability.

• Hands-on experience with AWS Batch and AWS Step Functions for workflow orchestration and automation.

• Strong understanding of AWS services including ECS, ECR, Docker, CloudWatch, and Athena.

• Ability to design, build, and maintain scalable cloud-based data engineering solutions.

• Experience in developing efficient and reliable data pipelines in cloud environments.

• Collaborate with cross-functional teams to support data integration and analytics requirements.

• Troubleshoot and optimize data workflows to improve performance and reliability.