Spark Developer - C10 - Chennai

ETL Developer will be responsible for designing, implementing, and optimizing distributed data processing jobs to handle large-scale data in Hadoop Distributed File System(HDFS) using Apache Spark and Python. This role required deep understanding of data engineering principles, proficiency in Python and hands-on experience with Spark and Hadoop ecosystems. Developer will collaborate with data engineers, analysts, and business stakeholders to process, transform and drive insights and data driven decisions.

Responsibilities:

• Data Processing and Transformation:

  
  Design and Implement of Spark applications to process and transform large datasets in HDFS.

  Develop ETL Pipelines in Spark using Python for data Ingestion, cleaning, aggregation, and transformations.

  Performance Optimization:

  
  Optimize Spark jobs for efficiency, reducing run time and resource usage.

  Finetune memory management, caching, and partitioning strategies for Optimal performance

  Data Engineering with Hadoop and Spark:

  
  Load data from different sources into HDFS, ensuring data accuracy and integrity.

  Integrate Spark Applications with Hadoop frameworks like Hive, Sqoop etc.

  Testing and debugging:

  
  Troubleshoot and debug Spark Job failures, monitor job logs, and Spark UI to Identify Issues.

Qualifications:

• 2-5 years of relevant experience
• Experience in programming/debugging used in business applications
• Working knowledge of industry practice and standards
• Comprehensive knowledge of specific business area for application development
• Working knowledge of program languages
• Consistently demonstrates clear and concise written and verbal communication
• Expertise in handling complex large-scale Warehouse environments
  

  • Hands-on experience writing complex SQL queries, exporting and importing large amounts of data using utilities

Education:

• Bachelor's degree in a quantitative field (such as Engineering, Computer Science) or equivalent experience

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

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