EIM Data Analyst

VirtusaIrving, TX

About The Position

6+ years of experience in Developing and maintaining scalable software applications using Python and PySpark for large-scale data processing and analytics. Design and implement efficient Big Data solutions, including distributed data pipelines and batch/stream processing systems. Collaborate with cross-functional teams to define requirements, design architecture, and deliver high-quality software components. Ensure code quality through best practices such as unit testing, code reviews, and version control, while maintaining clear documentation. Monitor, troubleshoot, and optimize application performance, focusing on scalability, reliability, and efficient resource utilization in Big Data environments.

Requirements

  • 6+ years of experience in developing and maintaining scalable software applications using Python and PySpark for large-scale data processing and analytics.
  • Experience in designing and implementing efficient Big Data solutions, including distributed data pipelines and batch/stream processing systems.
  • Experience collaborating with cross-functional teams to define requirements, design architecture, and deliver high-quality software components.
  • Experience ensuring code quality through best practices such as unit testing, code reviews, and version control, while maintaining clear documentation.
  • Experience monitoring, troubleshooting, and optimizing application performance, focusing on scalability, reliability, and efficient resource utilization in Big Data environments.

Responsibilities

  • Develop and maintain scalable software applications using Python and PySpark for large-scale data processing and analytics.
  • Design and implement efficient Big Data solutions, including distributed data pipelines and batch/stream processing systems.
  • Collaborate with cross-functional teams to define requirements, design architecture, and deliver high-quality software components.
  • Ensure code quality through best practices such as unit testing, code reviews, and version control, while maintaining clear documentation.
  • Monitor, troubleshoot, and optimize application performance, focusing on scalability, reliability, and efficient resource utilization in Big Data environments.
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