AWS Data Engineer

As an AWS Data Engineer, you will be responsible for designing, building, and optimizing data pipelines and scalable data assets. Your key responsibilities will include: - Designing, building, and optimizing data pipelines and scalable data assets. - Developing and maintaining high-performance code using PySpark/Python with best practices. - Performing code optimization using Spark SQL and PySpark for efficiency. - Implementing code refactoring to modernize legacy codebases for readability and maintainability. - Writing and maintaining unit tests (TDD) to ensure code reliability and reduce bugs. - Debugging and resolving complex issues including performance, concurrency, and logic flaws. - Working with AWS services (S3, EC2, Lambda, Redshift, CloudFormation) to architect and deliver solutions. - Managing version control and artifact repositories with Git and JFrog Artifactory. Qualifications Required: - 7+ years of strong hands-on experience in PySpark, Python, Boto3, and Python frameworks/libraries. - Expertise in Spark SQL & PySpark optimization. - Solid understanding of AWS architecture and cloud-native solutions. - Proficiency in Git repositories & JFrog Artifactory for code versioning. - Strong experience in refactoring, debugging, and optimizing legacy and new code. - Knowledge of TDD/Unit testing to ensure robust solutions.,