Description

You will build and maintain large-scale data processing systems and pipelines.

This role is on-site.

Responsibilities

• Design and maintain ETL workflows and data pipelines using Hadoop technologies.
• Develop and optimize large-scale data processing jobs with Apache Spark.
• Manage structured data efficiently within HDFS and Hive environments.
• Ensure data quality, reliability, and performance tuning across all pipelines.
• Support batch and near real-time data ingestion using Sqoop or Kafka.

Required Skills

• 5+ years of hands-on experience in Big Data and Hadoop platform development.
• Proficiency with Hadoop and Apache Spark.
• Experience building ETL and Data Pipelines.
• Working knowledge of HDFS, Kafka, and Sqoop.
• Skills in Performance Tuning and Analytics.
• Experience managing Big Data workloads.

Preferred Skills

• Experience with data quality management and reliability engineering.
• Structured data processing in Hive.

Key Skills

Education

Any Graduate