Description

You will design and implement scalable, distributed data architectures for large-scale processing.

This role is on-site.

Responsibilities

• Design and maintain distributed data architectures for high-volume processing.
• Implement and optimize data storage solutions using Hadoop and Spark.
• Develop efficient ETL processes using PySpark for data extraction, transformation, and loading.
• Optimize PySpark applications for performance, scalability, and resource management.

Required Skills

• 6+ years of experience as a Big Data Engineer.
• Strong proficiency in PySpark for ETL processes and data transformations.
• Expertise in Python and core Big Data technologies.
• Deep understanding of Big Data processing frameworks.
• Experience with distributed computing and parallel processing.
• Proven track record in managing complex ETL processes.
• Any Graduate degree.

Preferred Skills

• Experience optimizing PySpark applications for resource management.
• Deep knowledge of Hadoop ecosystem components.

Key Skills

Education

Any Graduate