Description

Key Responsibilities:

  • Big Data Architecture: Design, develop, and maintain scalable and distributed data architectures capable of processing large volumes of data.
  • Data Storage Solutions: Implement and optimize data storage solutions using technologies such as Hadoop, Spark, and PySpark.
  • PySpark Development: Develop and implement efficient ETL processes using PySpark to extract, transform, and load large datasets.
  • Performance Optimization: Optimize PySpark applications for better performance, scalability, and resource management.

Qualifications:

  • Proven experience as a Big Data Engineer with a strong focus on PySpark.
  • Deep understanding of Big Data processing frameworks and technologies.
  • Strong proficiency in PySpark for developing and optimizing ETL processes and data transformations.
  • Experience with distributed computing and parallel processing.
  • Ability to collaborate in a fast-paced, innovative environment.

Skills:

 

Big Data, Pyspark

Key Skills
Education

Any Graduate

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