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• Nitesht Pamulapati
• Nitesht Pamulapati
• mohanravipudi@gmail.com
• Sadiya Ahmad
• Nitesht Pamulapati
• mohanravipudi@gmail.com
• Nitesht Pamulapati

• Monitoring the issue with the production jobs, verifying logs for accuracy and timeliness of execution.

• Reporting the production issues and suggesting the enhancements or fix plan according.

• Developed the enhancements and bug fixes for production issues.

• Co-ordinate with build and release team for production readiness of fixes and enhancements.

• Ingesting the data from different databases like SQL, Oracle into Hadoop Data Lake using Sqoop. Writing Pig and Hive scripts to process the HDFS data.

• Extensively worked on creating partitions, UDF’s, Performance tuning, Compression- related properties in Hive.

• Debugging and performance tuning of Pig and hive jobs.

• Gathering Business requirements and preparing detailed specifications that follows project guidelines which are required to develop programs.

• Writing several Shell scripts for cleansing and preparing the data before it is moved to Hadoop Data Lake.

• Performance tuning of Sqoop for optimizing the time taken to importing the data into Hadoop.

• Exporting data from Hadoop to different data sets.

• Implemented Spark using Python (pySpark) and SparkSQL for faster testing and processing of data.

• Worked on Spark with Python and Scala.

• Transforming the data according to the data set before exporting the data from Hadoop.

• Writing pig scripts at transformation stage which take place before exporting data. 

• Writing Sqoop queries for exporting the data in Teradata and Sql server databases.

• Created jar files to handle many limitations in the framework.

• Involved in loading data from Teradata database into HDFS using Sqoop queries.

• Involved in submitting and tracking MapReduce jobs using Job Tracker.

• Involved in creating Oozie workflow and Coordinator jobs to kick off the jobs on time for data availability.

• Used Pig as ETL tool to do transformations, event joins, filter and some pre-aggregations

• Implemented business logic by writing Pig UDFs in Java and used various UDFs from Piggybanks and other sources

Implemented Hive Generic UDF's to implement business lo