PROFESSIONAL SUMMARY:

• Above 8+ years’ experience as Big Data/Hadoop developer and java Developer in Hadoop Ecosystem using Spark, Scala, Hive, HBase, Pig, Sqoop and Java for complex business problems, which involves real time effective analysis and processing of semi - structured and unstructured data.
• Experience in Hadoop, Big Data and Java technologies such as HDFS, MapReduce, Apache Pig, Impala, Hive, HBase, Sqoop, Flume, Oozie, Spark, Storm, Kafka, AWS, Amazon EMR, Zookeeper, Oracle, JSP, JDBC and Spring.
• Strong noledge on implementation of SPARK core - SPARK SQL, MLlib, GraphX and Spark streaming
• Good Knowledge in Amazon AWS concepts like EMR and EC2 web services which provides fast and efficient processing
• Expertise in developing both Front End & Back End applications using Java, Servlets, JSP, Web Services, Struts, Hibernate, JDBC, JavaScript, JSON, HTML, and XML.
• Experience with Oozie Workflow Engine in running workflow jobs with actions that run Hadoop MapReduce and Pig jobs
• Strong noledge of Pig and Hive's analytical functions, extending Hive and Pig core functionality by writing custom UDFs.
• Hands on experience in writing Ad-hoc Queries for migrating data from HDFS to HIVE and analyzing the data using HiveQL.
• Strong Experience in working with Databases like Oracle, and MySQL, Teradata, Netezza and proficiency in writing complex SQL queries.
• Strong experience on Hadoop distributions like Cloudera, MapR and Hortonworks.
• Good understanding of NoSQL databases and hands on work experience in writing applications on NoSQL databases like HBase, Cassandra and MongoDB.
• Hands on experience in Import/Export of data using Hadoop Data Management tool SQOOP.
• Proficient in configuring Zookeeper, Cassandra & Flume to the existing Hadoop cluster
• Written multiple MapReduce programs in Python for data extraction, transformation and aggregation from multiple file formats including XML, JSON, CSV and other compressed file formats.
• Experienced working with JIRA for project management, GIT for source code management, JENKINS for continuous integration and Crucible for code reviews.
• Strong Experience on writing SQL Queries, PL/SQL, JPA that includes Procedures, functions, triggers, cursors and packages.
• Implemented Service Oriented Architecture (SOA) using Web Services and JMS (Java Messaging Service).
• Implemented J2EE Design Patterns such as MVC, Session Façade, DAO, DTO, Singleton Pattern, Front Controller and Business Delegate.
• Experience in Full SDLC cycle which involves architecture, analysis, design, development, testing, Implementation, deployment, Enhancements, and production support using Agile and Waterfall Methodologies.
• Experienced with IDE’s like RAD, Eclipse, STS, and Net Beans etc.
• Experienced with various application / web servers like WebSphere, JBoss, WebLogic, and Tomcat.
• Experience as frond end developer.
• Experience in front end technologies like HTML5, CSS3, JavaScript, JQuery, XQuery, AngularJS and KnockoutJS.
• Exposure building Java applications using tools like ANT, MAVEN and Gradle.
• Proficient in Core Java concepts like Multi-threading, Collections and Exception Handling concepts.
• Experience in version control tools like SVN, GitHub and CVS.
• Experience of developing applications with Model View Architecture (MVC2) using Spring Framework and J2EE Design Patterns.
• Strong team player with good communication, analytical, presentation and inter-personal skills.
• Experience working with data lake is a system or repository of data stored in its natural/raw format, usually object blobs or files.
• Working with data lake is usually a single store of all enterprise data including raw copies of source system data and transformed data used for tasks such as reporting, visualization, advanced analytics and machine learning.

TECHNICAL SKILLS:

Big Data Technologies: Hadoop, MapReduce, Hive, Pig, HBase, Impala, Hue, Sqoop, Kafka, Storm, Oozie, Flume.

Frame Works: Spring, Struts, Hibernate 4.3, EJB 2.0 / 3.0, Web Services, SOAP, Restful, JMS.

Java Technologies: Java, J2EE, JDBC, Servlets, JSP, JavaBeans, EJB, JPA, JMS, Web Services.

Spark components: RDD, Spark SQL (Data Frames and Dataset), Spark Streaming.

Cloud Infrastructure: AWS Cloud Formation, S3, EC2-Classic and EC2-VPC.

Programming Languages: SQL, C, C++, Java, Core Java and Python.

Databases: Oracle 12c/11g, Teradata 15/14, MySQL, SQL Server2016/2014, DB2.

Scripting and Query Languages: Shell scripting, PL/SQL, Java Script, HTML5/4, DHTML, CSS3/2, JQuery.

XML Technologies: DTD, XSD, XML, XSL, XSLT, XQuery, SAX, DOM, JAXP.

Version Control: CVS, SVN and Clear Case.

Operating Systems: Windows, UNIX/Linux

Application/Web Servers: WebSphere, Web Logic, Apache, Tomcat, JBOSS.

Build Tools: Eclipse, ANT 1.7, Maven, NetBeans, IBM Rational Application Developer

PROFESSIONAL EXPERIENCE:

Confidential, Columbus, OH

Big-Data Hadoop Developer with Java

Responsibilities:

• To perform high level analysis and design software for new and existing systems.
• Experience with test automation strategies and design practices.
• Expertise with large-scale search systems including algorithm strategies and measure success, optimization.
• Working on BigData-Hadoop infrastructure for batch processing.
• Strong experience on Hadoop distributions like Cloudera and Hortonworks Platforms.
• Used Spark API over Hortonworks Hadoop YARN to perform analytics on data in Hive.
• Responsible for building scalable distributed data solutions using Hadoop.
• Participate in unit, system & acceptance testing by designing tests, building test data.
• Hands on experience in Import/Export of data using Hadoop data management tool SQOOP.
• Developed scalable, Hadoop-based data processing algorithms using MapReduce, HBase and Hadoop ecosystem.
• Along with making recommendations/improvements/fixes to the tested system
• Plan and assist in load, capacity, and performance analysis and/or testing.
• Involved in developing spark application to perform ETL kind of operations on the data.
• Used Apache TEZ TEMPhas an execution engine for building high performance batch and interactive data processing applications, coordinated by YARN in Apache Hadoop .
• Developed Data-governance tools using pyspark for securely placing enterprise data.
• Participate in the analysis and implementation of third-party solutions for Confidential applications with the ability to understand the impact and analyze the risk.
• Installed/Configured/Maintained Apache Hadoop clusters for application development and Hadoop tools like Hive, Pig, HBase, Flume, Oozie and Sqoop.
• Work with others to design solutions for both offline batch processes and web-based applications.
• Created and maintained various Shell and Python scripts for automating various processes and optimized MapReduce workloads and performance tuning and analysis.
• Used SQOOP to import Teradata data to HDFS.
• Used cloud computing on the multi-node cluster and deployed Hadoop application on cloud S3 and used Elastic Map Reduce (EMR) to run a Map-reduce.
• Worked extensively with big-data tools, integrating Apache Solr search for multi-faced search.
• Hands on experience with NoSQL databases like HBase, Cassandra for POC (proof of concept) in storing.
• Leveraged strong skills in developing applications involving Hadoop, Map Reduce, Yarn, Flume, Hive, H Base, Cloudera,
• Developed Spark scripts by using Scala shell commands and PySpark as per the requirement.
• Develop the YAML based ETL jobs that would ensure fault tolerant ways of Data Ingestion, Data Integration, Transformation using Sqoop, Hive, Spark and Shell Scripting.
• Provided input on database design and building stored procedures for smooth data.
• Developed the core search module using the Apache Solr and customized the Apache Solr for handling fallback searching and to provide custom functions.
• Worked on creating mini-Solr Cloud cluster tool for testing purpose used by team.
• Created HBase tables to load large sets of structured and unstructured data coming from UNIX, NoSQL and a variety of portfolios.
• Developed Map reduce programs for the files generated by hive query processing to generate key, value pairs and upload the data to NoSQL database HBase.
• Integrated Hive with HBase to upload data and perform row level operations.
• Worked on NoSQL database HBase to perform operations on sparse data set.
• Worked on Hive SQL for faster execution of Hive queries.
• Developed and executed HIVE queries on HUE browser.
• Worked and used transformations, cleaning and filtering on imported data using Hive, Map Reduce, and loaded final data into HDFS .
• Developed Kafka consumer's API in Python and Pyspark for consuming data from Kafka topics.
• Written Test Cases using Java which includes Hive-runner and JQ plugins.
• Worked with LINUX OS in-order to write Test Cases.
• Using TEZ improves the MapReduce paradigm by dramatically improving its speed, while maintaining MapReduce's ability to scale to petabytes of data.
• Used Spark Context to create RDDs to use incoming data to perform Spark Transformations and Actions.
• Created Spark SQL Context to load data from Parquet, JSON files and perform SQL queries.
• Worked with Hive file formats such as ORC, sequence file, text file partitions and buckets to load data in tables and perform queries.
• Created/Inserted/Updated Tables in Hive using DDL, DML commands.

Environment: Hadoop, H-Base, Hive, Spark, Kafka, ETL, Apache Solr, Apache Lucene, Java, XML, Map Reduce, JIRA.

Confidential, San Antonio, TX

Sr. Big Data Hadoop Engineer / Database Applications

Responsibilities:

• Facilitate the review and analysis of business requirements.
• Design and engineer solutions for new and existing applications.
• Create and maintain functional / technical design specifications and solutions to satisfy project requirements.
• Provides technical and design expertise to the project team regarding applications solutions and problem resolution.
• Develop software to specifications.
• Identify and implement automation strategies in the SDLC process that enables high quality, faster delivery of new solutions to our business users.
• Successfully export large data sets from RDBMS to hive data warehouse using Sqoop techniques for make use of Hive QL.
• Embrace and be a strong advocate for CI/CD and agile practices
• Participate in vendor software evaluations and integration strategies.
• Mentor and guide others in you're team
• Design, development and implementation of ETL pipelines using python API (PYspark) of Apache spark on AWS
• Automate ETL jobs with both event and schedule-based techniques using AUTOMIC tool.
• Runs code and design reviews and technical presentations to cross functional staff.
• Provides 24/7 on-call rotational support of applications support to users including issue resolution. Accurately repairs and documents changes to applications as assigned.
• Monitors system and application performance and troubleshoot/ resolve escalated issues.
• Establish a high-performing Agile / Continuous Integration engineering practice.
• Continuous monitoring and managing the Hadoop cluster through Cloudera Manager
• Continually seek ways to optimize and improve all operational aspects of our IT solutions.
• Successfully export large data sets from RDBMS to hive data warehouse using Sqoop techniques for make use of Hive QL.
• Created tables in HBase to store variable data formats of PII data coming from different portfolios
• Built an end-to-end automated ETL data pipeline and deployed in MapR cluster which process data every month and performs extracting zip files, load the data into respective hive tables in compressed format using shellscript, pyspark RDD and run QC.
• Worked on Hive SQL for faster execution of Hive queries using AWS EMR.
• Worked with GIT CI/CD process to trigger the pipelines in order to generate DATA FILES.
• Developed HIVE scripts to extract data from DE Team S3 buckets.
• Worked with HDFS commands to copy DATA from S3 bucket.
• Written Test Cases using Java which includes Hive-runner and JQ plugins.
• Developed and executed HIVE queries on HUE browser.
• Develop ETL processes in Python to send large data sets into Hadoop and bring summarized results back into the SQL data warehouse
• Designed, developed and implemented data masking methods and techniques including to safeguard sensitive data such as PII in accordance with HIPAA Laws
• Developed Map Reduce/Pyspark modules for predictive analytics & machine learning in Hadoop on AWS
• Used Apache TEZ TEMPhas an execution engine for building high performance batch and interactive data processing applications, coordinated by YARN in Cloudera, Apache Hadoop .
• Using TEZ improves the MapReduce paradigm by dramatically improving its speed, while maintaining MapReduce's ability to scale to petabytes of data.
• Worked with LINUX OS in-order to write Test Cases.
• Has worked using AMAZON S3 services to store and retrieve data from S3 buckets.
• Developed and executed HIVE scripts in AWS ATHENA.
• Worked using shell-scripting to deploy clusters and send data files as per the specifications given by label providers.
• Worked using JSON files for running the HIVE scripts and in retrieving the data after completion of the CI/CD pipelines.

Environment: Hadoop, HDFS, Hive, AWS EMR, AWS Athena, AWS S3, UNIX Shell ScriptingJson, GIT CI/CD Integration, Map Reduce, Tez, Java, Linux OS.

Confidential, Austin, TX

Sr. BigData / Hadoop Developer

Responsibilities:

• Working on BigData infrastructure for batch processing as well as real-time processing. Responsible for building scalable distributed data solutions using Hadoop.
• Installed/Configured/Maintained Apache Hadoop clusters for application development and Hadoop tools like Hive, Pig, HBase, Flume, Oozie and Sqoop.
• Strong experience on Hadoop distributions like Cloudera and Hortonworks Platforms.
• Developed Pig Latin scripts to extract the data from the web server output files to load in HDFS.
• Worked on Apache Spark SQL and Data frames for faster execution of Hive queries using Spark.
• Created HBase tables to load large sets of structured and unstructured data coming from UNIX, NoSQL and a variety of portfolios.
• Transform the logs data into data model using Pig and written UDF's functions to format the logs data.
• Developing ETL jobs with organization and project defined standards and processes
• Migrated an existing on-premises application to AWS.
• Used AWS services EC2 and S3 for small data sets processing and storage.
• Successfully export large data sets from RDBMS to hive data warehouse using Sqoop techniques for make use of Hive QL.
• Involved in generating the reports of the results of the scripts to analyze the necessities by using data visualization toll tableau.
• Designed and implemented custom writable, custom input formats, custom partitions and custom comparators in Cloudera and MapReduce.
• Involved in converting Hive/SQL queries into Spark transformations using Spark RDD, Scala and Python.
• Developed pig scripts to transform the data into structured format and it are automated through Oozie coordinators.
• Worked on Spark SQL and Data frames for faster execution of Hive queries using Spark and AWS EMR
• Developed Map reduce programs for the files generated by hive query processing to generate key, value pairs and upload the data to NoSQL database HBase.
• Responsible for troubleshooting issues in the execution of MapReduce jobs by inspecting and reviewing log files.
• Involved in POC for migrating RDBMS and ETL from Hive to Spark in Spark on Yarn Environment.
• Worked and used transformations, cleaning and filtering on imported data using Hive, Map Reduce, and loaded final data into HDFS
• Implemented installation and configuration of multi-node cluster on the cloud using Amazon Web Services (AWS) on EC2.
• Conducted data analysis with basic Python and wrangled data for data repositories.
• Configured Hive Meta store to use Oracle database to establish multiple user connections to hive tables.
• Used Restful web services using JAX-RS and used DELETE, PUT, POST, GET HTTP methods
• Worked using scalable and high-performance web services for data tracking and done High-speed querying.
• Used Spark API over Hortonworks Hadoop YARN to perform analytics on data in Hive.
• Used Java Messaging Services (JMS) for reliable and asynchronous exchange of important information such as payment status report on IBM WebSphere MQ messaging system.
• Used cloud computing on the multi-node cluster and deployed Hadoop application on cloud S3 and used Elastic Map Reduce(EMR) to run a Map-reduce.
• Implemented the workflows using Apache Oozie framework to automate tasks.
• Collaborated with the infrastructure, network, database, application and BI teams to ensure data quality and availability.
• Maintaining and monitoring clusters, Loaded data into the cluster from dynamically generated files using Flume and from relational database management systems using Sqoop.
• Involved in importing the real-time data to Hadoop using Kafka and implemented the Oozie job for daily imports.
• Implemented CRUD operations using CQL on top of Cassandra file system.

Environment: Hadoop, HDFS, Spark, Strom, AWS Kafka, Oracle 12c, Map Reduce, Hive, Pig, Sqoop, Oozie, HBase, Cassandra, MongoDB, Tableau, DB2, Java, Python, Splunk, UNIX Shell Scripting.

Confidential, Foster city, CA

Sr. Hadoop Developer

Responsibilities:

• Imported data to HDFS from MySQL and exported data from HDFS to MySQL data, using Apache Sqoop.
• Modified and Optimized databases to speed up importing to HDFS
• Performed data analysis of online secure data by importing data to HDFS using Apache Flume.
• Used SQOOP to import Teradata data to HDFS.
• Worked on Cloudera Platform.
• Extracted, modified and loaded data from files, MySQL, Oracle and other input sources to load data into HDFS.
• Cleaned data and preprocessed data using MapReduce for efficient data analysis
• Used Scala and Java to develop MapReduce programs for data cleansing and analysis
• Developed custom UDFs using Apache Hive to manipulate data sets
• Created Hive Compact/ Bitmap Indexes to speed up the processing of data
• Created/Inserted/Updated Tables in Hive using DDL, DML commands
• Improved performance of datasets for querying through
• Worked with Hive file formats such as ORC, sequence file, text file partitions and buckets to load data in tables and perform queries
• Used Pig Custom Loaders to load different from data file types such as XML, JSON and CSV
• Developed PIG Latin scripts to extract the data from the web server output files and to load into HDFS
• Configured Hadoop clusters on AWS.
• Experience in AWS - S3, EC2, Redshift
• Scheduled workflow of jobs using Oozie to perform sequential and parallel processing
• Worked on NoSQL database HBase to perform operations on sparse data set
• Developed shell scripts, python scripts to check the health of Hadoop Daemons and schedule jobs
• Integrated Hive with HBase to upload data and perform row level operations
• Experienced in creating Spark Context and performing RDD transformations and actions using Python API
• Used Spark Context to create RDDs to use incoming data to perform Spark Transformations and Actions
• Created Spark SQL Context to load data from Parquet, JSON files and perform SQL queries
• Created data frames out of text files to execute Spark SQL queries
• Used Spark's enable Hive Support to execute Hive queries in Spark
• Created DStreams on incoming data using createstream
• Experience working with Hadoop distribution of Hortonworks and highly capable in installing and managing roles.
• Developed Spark streaming applications to work with data generated by sensors in real time
• Used Spark API over Hortonworks Hadoop YARN to perform analytics on data in Hive.
• Linked Kafka and Flume to Spark by adding dependencies for data ingestion
• Performed data extraction, aggregation, log analysis on real time data using Spark Streaming
• Created Broadcast and Accumulator variables to share data across nodes
• Used case classes, higher order functions, collections of Scala to apply map transformations on RDDs
• Integrated Hadoop Security with Active Directory for authentication and authorization
• Used Scala to develop Scala coded spark projects and executed using spark-submit
• Leveraged option monad with Some and None in Scala to avoid null pointer exceptions
• Implemented Pattern matching in Scala to identify the desired sensor type for performing analysis
• Developed Scala-Traits to reuse code in other classes

Environment: HDFS, MapReduce, Hive, Hadoop distribution of Horton Works, HBase, Impala, AWS Pig, Java, Oozie, Scala, Kafka, Spark, Active Directory Integration, Git, Maven, Talend, Putty, CentOS 6.4, SBT.

Confidential - Detroit, MI

Hadoop Developer

Responsibilities:

• Wrote PIG scripts using various input and output formats. Also designed custom format as per the business requirements.
• Used SQOOP to dump data from MySQL relational database into HDFS for processing and exporting data to RDMS.
• Developed workflow in Oozie to automate the tasks of loading the data into HDFS and pre-processing, analyzing and testing the classifier using MapReduce, Pig and Hive jobs.
• Integrated Oozie with the rest of the Hadoop stack supporting several types of Hadoop jobs out of the box (like, Pig, Hive, and Sqoop) as well as system specific jobs (such as Perl and shell script).
• Automated all the jobs, for pulling data from relational databases to load data into Hive tables, using Oozie workflows and enabled email alerts on any failure cases.
• Involved in migrating the map reduce jobs into Spark Jobs and Used Spark SQL and Data frames API to load structured and semi structured data into Spark Clusters
• Worked on SPARK engine creating batch jobs with incremental load through STORM, KAFKA, SPLUNK, FLUME.
• Worked with Kafka for the proof of concept for carrying out log processing on a distributed system
• Used SparkSQL for Scala & Python interface that automatically converts RDD case classes to schema RDD
• Tool monitored log input from several datacenters, via Spark Stream, was analyzed in Apache Storm and data was parsed and saved into Database.
• Used tools like SQOOP, Kafka to ingest data into Hadoop
• Implemented Database access through JDBC at Server end with Oracle.
• Used Spring Aspect Oriented Programming (AOP) for addressing cross cutting concerns.
• Developed request/response paradigm by using Spring Controllers, Inversion of Control and Dependency Injection with Spring MVC.
• Used CVS for version control and Log4j for logging.
• Used Neo4j to understand the connectivity between the elements in data model.
• Used Pig and Hive in the analysis of data.
• Extracted files from NoSQL database like Cassandra, MongoDB using Sqoop.
• Worked with Flume to import the log data from the reaper logs and syslog's into the Hadoop cluster.
• Used complex data types like bags, tuples, and maps in Pig for handling data.
• Created/modified UDF and UDAFs for Hive whenever necessary.
• Involved in managing running and pending tasks Map Reduce through Cloudera manager console.
• Developed PigUDFs for preprocessing thee data for analysis.
• Involved in writing shell scripts for scheduling and automation of tasks.
• Managed and reviewed Hadoop log files to identify issues when job fails.
• Hands on experience with NoSQL databases like HBase, Cassandra for POC (proof of concept) in storing
• URL's, images, products and supplements information at real time.
• Worked on Hive for analysis and generating transforming files from different analytical formats to text files.
• Used Hue for UI based PIG script execution, Oozie scheduling
• Involved in writing Hive queries for data analysis with respect to business requirements.
• Also assisted admin team in installation and configuration of additional nodes in Hadoop cluster

Environment:: Apache Hadoop (Gen 1), AWS, Hive, Pig, Sqoop, Oozie, HBase, Map-Reduce(MR1), Cloudera, HDFS, Flume, Hue, Linux, HTML5 & CSS3, Hadoop2.2, JQuery, Neo4j, Maven, MongoDB, Java, JDK1.6, J2EE, JDBC, Spring 2.0, Hibernate 4.2.

Confidential, Warren, NJ

Hadoop Developer

Responsibilities:

• Configured Apache Hadoop clusters for application development and Hadoop tools: Hive, Pig, HBase, Zookeeper and Sqoop.
• Developed shell scripts to monitor the health check of Hadoop daemon services and respond accordingly to any warning or failure conditions.
• Collecting and aggregating large amounts of log data using Apache Flume and staging data in HBASE/HDFS for further analysis.
• Collected the logs data from web servers and integrated with HBASE using Flume.
• Installed Oozie workflow engine to run multiple Hive and Pig Jobs.
• Used Sqoop to import and export data from HDFS to RDBMS and vice-versa.
• Created Hive tables, data loading and developed Hive UDFs
• Used Hive to analyze the partitioned and bucketed data and compute various metrics for reporting
• Gained noledge on building Apache Spark applications using Scala
• Used Spark SQL, Spark Mlib, Spark Streaming for data streaming and analysis.
• Developed Scala program for data extraction using Spark Streaming
• Worked on importing and exporting data from Oracle and DB2 into HDFS and HIVE using Sqoop
• Created Hive External tables on the existing HDFS file systems.
• Developed shell scripts for rolling day-to-day processes and automation
• Developed POC for Apache Kafka
• Automated workflows using shell scripts pull data from various databases into Hadoop.
• Developed scalable, Hadoop-based data processing algorithms using MapReduce, Pig, Hive, HBase and the Hadoop ecosystem
• Deployed Hadoop Cluster in Fully Distributed and Pseudo-distributed modes.
• Setup QA environment and updating configurations for implementing scripts with Pig, Hive and Sqoop.
• Transform massive amounts of raw data into actionable analytics
• Developed scripts to automate the process and generate reports.
• Installed, optimized and configured new servers and application upgrades in existing network environment to meet the requirements.
• Provided User training and support.

Environment: Hadoop, MapReduce, Spark, Java, Hive, HDFS, PIG, Sqoop, Kafka, Oozie, Flume, HBase, Zookeeper, CDH4&CDH5,Oracle,Perl, PL/SQL, Python, Linux.

Confidential

Java Developer

Responsibilities:

• Developed various UML diagrams like use cases, class diagrams, interaction diagrams (sequence and collaboration) and activity diagrams.
• Developed the Object-Oriented Analysis & Design approach for the project using object-oriented paradigm throughout life cycles.
• Responsible for designing and implementing the web tier of the application from inception to completion using J2EEtechnologies such as MVC framework, Servlets, JavaBeans, JSP.
• Developed the application using Struts Framework that leverages classical Model View Layer (MVC Model2) architecture.
• Implemented Business processes such as user authentication, Account Transfer using Session EJB.
• Implemented Hibernate for O/R mapping and persistence.
• Worked on Creative Suite 3 and Creative Suite 4 for creating websites and presentations.
• Involved in the components styling (CSS) and skinning.
• Involved in multi-tiered J2EE design utilizing Spring IOC and Hibernate deployed on Websphere Application Server connecting to DB2 database.
• Used Java Messaging Services (JMS) for reliable and asynchronous exchange of important information such as payment status report.
• Developed JUnit test cases for all the developed modules.
• Extensively used DB2 Database to support the SQL.
• Used CVS for version control across common source code used by developers.
• Used Log4J to capture the log that includes runtime exceptions.
• Worked on event - driven modeling like Node.js for lightweight and efficient runtime built.
• Used JDBC to invoke Stored Procedures and database connectivity.
• Responsible for data reconciliation with EOD files using scheduled batch process.
• Responsible for system development using J2EE architecture.
• Used Spring Framework for dependency injection, transaction management and AOP.
• Involved in Springs MVC model integration for front-end request action controller.
• Developed by utilizing Spring, Hibernate, Struts, Oracle, JPA, JQuery, Java Script, Spring core.
• Used Spring ORM support, Hibernate for development of DAO layer.
• Involved in implementing the DAO pattern for database connectivity and Hibernate.
• Written SQL queries and did modifications to existing database structure as required for addition of new features.
• Involved in designing the database and developed Stored Procedures, triggers using PL/SQL.
• Conducted database and code tuning to improve performance of the application, used Bulk binds, in-line queries, Dynamic SQL, Analytics and Sub-query factoring etc.
• Involved in the JMS Connection Pool and the implementation of publish and subscribe using Spring JMS.
• Used JMS Template to publish and Message Driven POJO (MDP) to subscribe from the JMS provider

Environment: Windows, IBM WebSphere Application Server, Eclipse, Spring, Hibernate 3.0, Struts 1.2, EJB,DB2, Java 1.4/J2EE, JDBC, JSP, JSF, JavaScript, HTML, CSS, DHTML, AJAX, OOAD techniques, CS4, EJB, JDBC, JNDI 1.2,DOM, JMS 1.0.1, XML, Web Services, Node.js, POJO, DOM, ANT, Rational Rose Apache Axis, WSDL, PL/SQL,LOG4J, CVS