SUMMARY

• Over 5.6 years of professional IT experience and over 2.5 years of Hands - on expertise on Big Data Analytics using HDFS, Map Reduce, Pig, SQOOP and Hive for scalability, distributed computing and high performance computing.
• In depth understanding/knowledge of HADOOP Architecture and various components such as Job Tracker, Task Tracker, Name Node, Secondary Name Node, Data Node processes & concepts
• Experience in building, maintaining multiple HADOOP clusters (prod, dev etc.,) of different sizes and configuration and setting up the rack topology for large clusters
• Experience in optimization of Map reduces algorithm using combiners and partitioners to deliver the best results.
• Experience in Database design, Entity relationships, Database analysis, Programming SQL, Stored procedure’s PL/ SQL, Packages and Triggers in Oracle and SQL Server on Windows and UNIX.
• Worked on different OS like UNIX/Linux, Windows NT, Windows XP, and Windows 2K.
• Extending Hive and Pig core functionality by writing custom UDFs.
• Experience in data management and implementation of Big Data applications using HADOOP frameworks.
• Experience in designing, developing and implementing connectivity products that allow efficient exchange of data between our core database engine and the HADOOP ecosystem.
• Experience in importing and exporting data using SQOOP from HDFS to Relational Database Systems and vice-versa.
• Launching and Setup of HADOOP/ HBASE Cluster which includes configuring different components of HADOOP and HBASE Cluster.
• Experienced in loading data from UNIX file system to HDFS.
• Experienced on loading and transforming of large sets of structured, semi structured and unstructured data.
• Installed and configured Flume, Hive, Pig, SQOOP and OOZIE on the HADOOP cluster.
• Managing and scheduling Jobs on a HADOOP cluster.
• Performing tuning and troubleshooting of Map Reduce jobs by analyzing and reviewing HADOOP log files.
• Involved in defining job flows, managing and reviewing log files.
• Worked on installing cluster, commissioning & decommissioning of data nodes, name node recovery, capacity planning, and slots configuration.
• Reviewing existing HADOOP/HBASE architecture and identify areas for improvement in the areas of scalability, maintainability, and performance.
• Strong understanding of data warehouse methodologies and concepts.
• Clear understanding of RDBMS design concept.
• Have hands on experience on various DB platforms like Oracle, My SQL and MS SQL server.
• Progressive experience in Software Development including Requirements Gathering, Design, Development, Unit Testing, Implementation, Application Support/Maintenance and Documentation with ability to interact with individuals Confidential all levels.
• Excellent knowledge of industry standard methodologies like Software Development Life Cycle (SDLC), Iterative Software Development Life Cycle Process, Product Lifecycle Management, Agile/Scrum
• Possess excellent knowledge on cross platform and technologies, highly skilled in putting together different technologies and tools to provide the best solution.
• Passionate learner with strong analytical skills, who enjoys learning and experimenting new technologies as a hobby, also as and when required for the project work.

TECHNICAL SKILLS

Programming: Java, Java script, Xml, PIG Latin, SQL, HiveQL, Shell Scripting

Big Data: HADOOP, HDFS, Hive, SQOOP, Pig, Zookeeper, Flume and OOZIE

Data Base: My SQL, Oracle 9i, Ms SQL Server, H Base

Operating Systems: Windows 95/98/2000/XP/Vista/7/Unix/Linux/UBUNTU

OLAP/DSS Tools: Business Objects 4.0/ XI 3.1(R3.1)/R2/R1/6.x/5.x/5i/4.x, Central Management Console, Central Configuration Manager, Designer, Desktop Intelligence, Web intelligence, WebI Rich client, Report Conversion Tool, Translation Manager, Crystal Reports 2008/XI/ 10.0/9.0/8.0

Utility Tools Assistant: TOAD, SQL* Navigator, Developer 2000, SQL*Loader, SQL

Documentation tools: Ms Office.

PROFESSIONAL EXPERIENCE

Confidential, Bedminster, NJ

HADOOP Developer

Responsibilities:

• Analyzed HADOOP clusters, other analytical tools used in big data like Hive, Pig and databases like HBASE.
• Used HADOOP to build scalable distributed data solution
• Extracted feeds form social media sites such as FACEBOOK, Twitter using Flume
• Used SQOOP extensively to ingest data from various source systems into HDFS.
• Extracted feeds form social media sites such as FACEBOOK, Twitter using Flume
• Used SQOOP extensively to ingest data from various source systems into HDFS.
• Written Hive queries for data analysis to meet the business requirements
• Created Hive tables and worked on them using Hive QL.
• Installed cluster, worked on commissioning and decommissioning of Datanode, Namenode recovery, capacity planning, and slots configuration
• Assisted in managing and reviewing HADOOP log files
• Assisted in loading large sets of data (Structure, Semi Structured, Unstructured)
• Implemented HADOOP cluster on UBUNTU Linux
• Installed and configured Flume, SQOOP, Pig, Hive, HBase on HADOOP clusters
• Managed HADOOP clusters include adding and removing cluster nodes for maintenance and capacity needs.
• Wrote test cases in JUNIT for unit testing of classes
• Involved in templates and screens in HTML and JavaScript.

Environment: HADOOP, Apache Pig, Hive, SQL Server, SQOOP, Flume and Linux.

Confidential, Buffalo Grove, IL

Java /HADOOP Developer

Responsibilities:

• Analyzing the requirements for the C2C Project.
• Develop the C2C project screens and core functionality
• Provide Code reviews for C2C project
• Write complex Java code
• Involved in requirements gathering and designing, server side coding using Spring MVC, spring and Hibernate.
• Developed Batch jobs using Spring Batch framework.

Environment: Windows, Java, Java Script,Html5,CSS, jQuery/Angular JS, XML, Spring, Spring Batch, Hibernate,JBoss5/Glassfish, Maven, JUnit, Ant, SVN, Jasper/iReports, Oracle PL/SQL and SQLServer.

Confidential, Palo Alto, CA

HADOOP Developer

Responsibilities:

• Proactively monitored systems and services, architecture design and implementation of HADOOP deployment, configuration management, backup, and disaster recovery systems and procedures.
• Involved in analyzing system failures, identifying root causes, and recommended course of actions.
• Documented the systems processes and procedures for future references.
• Monitored multiple HADOOP clusters environments using Ambary.
• Installed and configured Flume, Hive, Pig, SQOOP and OOZIE on the HADOOP cluster.
• Used Flume to collect, aggregate, and store the web log data from different sources like web servers, network devices and pushed to HDFS.
• Analyzed the web log data using the HiveQL to extract number of unique visitors per day, page- views, visit duration, most purchased product on website.
• Exported the analyzed data to the relational databases using SQOOP for visualization and to generate reports for the BI team.
• Integrated OOZIE with the rest of the HADOOP stack supporting several types of HADOOP jobs out of the box (like JAVA Map Reduce, Pig, Hive, SQOOP) as well as system specific jobs (such as JAVA programs)
• Developed application component interacting with MongoDB.
• Developed entire data transfer model using SQOOP framework
• Developed functionally equivalent batches using Hive

Environment: HADOOP, Hive, Pig, SQOOP, Zookeeper, Flume, OOZIE, Linux, Eclipse.

Confidential, Decatur, IL

HADOOP Developer

Responsibilities:

• Responsible for building scalable distributed data solutions using HADOOP.
• Responsible for Cluster maintenance, managing cluster nodes.
• Involved in managing and review of data backups and log files.
• Analyzed data using HADOOP components Hive and Pig.
• Hands on experience with ETL process.
• Involved in running HADOOP streaming jobs to process terabytes of data.
• Experienced in loading and transforming large sets of structured, semi-structured and unstructured data HADOOP concepts.
• Created Hive tables to store data and written Hive queries.
• Involved in importing data from various data sources, performed transformations using Hive, MapReduce, and loaded data into HDFS.
• Extracted the data from teradata into HDFS using SQOOP.
• Exported the patterns analyzed back to Teradata using SQOOP.
• Scheduled OOZIE workflow engine to run multiple Hive and Pig jobs, which independently run with time and data availability.

Environment: HADOOP, HDFS, Hive, Pig, SQOOP, OOZIE, Map Reduce, Cassandra, UNIX, Shell Scripting