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Sr. Big Data Developer Resume

Bartlesville, OklahomA

PROFESSIONAL SUMMARY:

  • Around 8 years of experience in software Admin and development, 4+ years of experience in developing large scale applications using Hadoop and Other Big data tools.
  • Experienced in the Hadoop ecosystem components like Hadoop Map Reduce, Cloudera, Hortonworks, HBase, Oozie, Hive, Sqoop, Pig, Flume, and Cassandra.
  • Extensive experience in analyzing data using Hadoop Ecosystems including HDFS, Hive, PIG, Sqoop, Flume, MapReduce, Spark, Kafka, HBase, Oozie, Solr and Zookeeper
  • Experience with distributed systems, large - scale non-relational data stores, MapReduce systems, data modeling, and big data systems.
  • Knowledge on implementing BigData in Amazon Elastic MapReduce (Amazon EMR) for processing, managing Hadoop framework dynamically scalable Amazon EC2 instances.
  • In depth understanding/knowledge of Hadoop Architecture and various components such as HDFS, Job Tracker, Task Tracker, NameNode, DataNode.
  • Experience with Amazon Web Services, AWS command line interface, and AWS data pipeline.
  • Experience in writing SQL, PL/SQL queries, Stored Procedures for accessing and managing databases such as Oracle, SQL Server2014/2012 MySQL, and IBM DB2.
  • Hands on experience on Database tuning and Query tuning.
  • Excellent understanding/knowledge of design and implementation of Teradata data warehousing solutions , Teradata Aster big data analytics and Analytic Applications.
  • Good working experience in using Spark SQL to manipulate Data Frames in Python .
  • Good knowledge in NoSQL databases including Cassandra and MongoDB.
  • Experience working on Cloudera, MapR and Amazon Web Services(AWS).
  • Excellent understanding of how Socket Programming enables two or more hosts to communicate with each other.
  • Involvement in creating custom UDFs for Pig and Hive to consolidate strategies and usefulness of Python/Java into PigLatin and HQL (HiveQL).
  • Planned and created answer for constant information ingestion utilizing Kafka, Storm, Spark spilling and different NoSQL databases.
  • Experience in handling native drivers of MongoDB, The Drivers which include Java and Python.
  • In depth understanding/knowledge of Hadoop Architecture and various components such as HDFS, JobTracker, Task Tracker, Name Node, Data Node and MapReduce concepts.
  • Extensive hands on experience in writing complex Mapreduce jobs, Pig Scripts and Hive data modeling.
  • Experience in converting MapReduce applications to Spark.
  • Good working knowledge in cloud integration with Amazon Web Services components like EMR, EC2, S3 etc.
  • Good working experience using Sqoop to import data into HDFS from RDBMS and vice-versa.
  • Good knowledge in using job scheduling and workflow designing tools like Oozie.
  • Experience in working with BI team and transform big data requirements into Hadoop centric technologies.
  • Experience in performance tuning the Hadoop cluster by gathering and analyzing the existing infrastructure.
  • Have good experience creating real time data streaming solutions using Apache Spark/Spark Streaming Apache Storm, Kafka and Flume.
  • Background with traditional databases such as Oracle, Teradata, Netezza, SQL Server, ETL tools processes and data warehousing architectures.
  • Experience in handling messaging services using Apache Kafka.
  • Experience in fine-tuning Mapreduce jobs for better scalability and performance.
  • Developed various Map Reduce applications to perform ETL workloads on terabytes of data.
  • Experienced in developing and implementing web applications using Java, J2EE, JSP, Servlets, JSF, HTML, DHTML, EJB, JavaScript, AJAX, JSON, JQuery, CSS, XML, JDBC and JNDI.
  • Working experience in Development, Production and QA Environments.
  • Possess strong skills in application programming and system programming using C++ and Python on Windows and LINUX platforms using principles of Object Oriented Programming (OOPS) and Design Patterns.
  • Experience in working with various Cloudera distributions (CDH4/CDH5) and have knowledge on Hortonworks and Amazon EMR Hadoop Distributions.
  • Working experience of control version tools like SVN, CVS, Clear Case and PVCS.

TECHNICAL SKILLS:

Big Data Technologies: HDFS, Hive, Hana, AWS, Map Reduce, Pig, Sqoop, Kafka, Storm, Oozie, Zookeeper, YARNAvro, EMR, Spark

Scripting Languages: Shell, Python, Perl, Scala

Tools: Quality center v11.0\ALM, TOAD, JIRA, HP QTP, HP UFT, Selenium, Test NG, JUnit

Programming Languages: Java, C.., C, SQL, PL/SQL, PIG-Latin, HQL,CQL

QA methodologies: Waterfall, Agile, V-model.

Front End Technologies: : HTML, XHTML, CSS, XML, JavaScript, AJAX, Servlets, JSP

Java Frameworks: MVC, jQuery, Apache Struts2.0, spring and Hibernate

Defect Management: Jira, Quality Center.

Domain Knowledge: GSM, WAP, GPRS, CDMA and UMTS (3G)

Web Services: SOAP (JAX-WS), WSDL, SOA, Restful (JAX-RS), JMS

Application Servers: Apache Tomcat, Web Logic Server, Web Sphere, JBoss

Version: controls: GIT, SVN, CVS

Databases: Oracle 11g, MySQL, MS SQL Server, IBM DB2 NoSQL Databases HBase, MongoDB Cassandra Data Stax Enterprise 4.6.1

Cassandra RDBMS: Oracle 9i, Oracle 10g, MS Access, MS SQL Server, IBM DB2, and PL/SQL

Operating Systems: Linux, UNIX, MAC, Windows NT / 98 /2000/ XP / Vista, Windows 7, Windows

PROFESSIONAL SUMMARY:

Confidential, Bartlesville, Oklahoma

Sr. Big Data Developer

Responsibilities:

  • Responsible for building scalable distributed data solutions using Hadoop .
  • Working as Hadoop Developer and admin in Hortonworks (HDP 2242) distribution for 10 clusters ranges from POC to PROD.
  • Responsible for Cluster maintenance, Monitoring, commissioning and decommissioning Data nodes, Troubleshooting, Manage and review data backups, Manage & review log files
  • Used Spark API over Cloudera Hadoop YARN to perform analytics on data in Hive.
  • Developed job processing scripts using Oozie workflow.
  • Installed Git lab for Code Respository..
  • Implemented various types of SSIS Transforms in Packages including Slowly Changing Dimension, lookup, Fuzzy Lookup, Conditional Split, Derived Column, Data Conversion etc.
  • Generated Tableau Dashboards Implementing Quick/Context filters, Parameters
  • Proficient with Tableau Server, Tableau Desktop, Tableau Online.
  • Expert in Strong understanding of dimensional data modeling, Strong SQL optimization capabilities, Metadata Management (Connections, Data Model, VizQL Model)
  • Skilled in Tableau Desktop for data visualization, Reporting and Analysis; Cross Map, Scatter Plots, Geographic Map, Pie Charts and Bar Charts, Page Trails and Density Chart.
  • Created HBase tables to store various data formats of data coming from different sources.
  • Installed and configured Hive, Pig, Sqoop, Flume and Oozie on the Hadoop cluster.
  • Configured Spark streaming to get ongoing information from the Kafka and stored the stream information to HDFS.
  • Developed data pipeline using Flume, Sqoop to ingest customer behavioral data and purchase histories into HDFS for analysis.
  • Utilized SparkSQL to extract and process data by parsing using Datasets or RDDs in HiveContext, with transformations and actions (map, flatMap, filter, reduce, reduceByKey).
  • Extend the capabilities of DataFrames using User Defined Functions in Python and Scala.
  • Resolve missing fields in DataFrame rows using filtering and imputation.
  • Integrate visualizations into a Spark application using Databricks and popular visualization libraries (ggplot, matplotlib).
  • Experienced on adding/installation of new components and removal of them through Ambari
  • Monitoring systems and services through Ambari dashboard to make the clusters available for the business
  • Architecture design and implementation of deployment, configuration management, backup, and disaster recovery systems and procedures
  • Worked with HQL and Criteria API from retrieving the data elements from database.
  • Hand on experience on cluster up gradation and patch upgrade without any data loss and with proper backup plans
  • Configured different Notifications on AWS Services.

Environment: HortonWorks 2.4.2, Git,Spark 1.6.2, Tableau, Spark ML, Hive 1.2.1, Sqoop 1.4.6, Flume 1.5.0, HBase 1.1.4, MySQL 5.6, Scala 2.11.x,Pyspark 1.4.0, AWS, Jenkins

Confidential, Pittusburg, PA

Sr. Big Data Developer

Responsibilities:

  • Extensively involved in installation and configuration of Cloudera Distribution Hadoop platform.
  • Extract, transform, and load (ETL) data from multiple federated data sources (JSON, relational database, etc.) with DataFrames in Spark.
  • Utilized SparkSQL to extract and process data by parsing using Datasets or RDDs in HiveContext, with transformations and actions (map, flatMap, filter, reduce, reduceByKey).
  • Extend the capabilities of DataFrames using User Defined Functions in Python and Scala.
  • Resolve missing fields in DataFrame rows using filtering and imputation.
  • Integrate visualizations into a Spark application using Databricks and popular visualization libraries (ggplot, matplotlib).
  • Train analytical models with Spark ML estimators including: linear regression, decision trees, logistic regression, and k-means.
  • Developed Spark application (Spark Core, Java 8, Spark Streaming, Apache Kafka, Yarn, HDFS) to read incoming files in near real time and process them within few seconds.
  • Created EC2 instances and implemented large multi node Hadoop clusters in AWS cloud from scratch.
  • Configured AWS IAM and Security Groups.
  • Developed terraform template to deploy Cloudera Manager on AWS.
  • Configured different Notifications on AWS Services.
  • Hands on experience in managing and monitoring the Hadoop cluster using Cloudera Manager.
  • Installed, configured Hadoop Cluster using Puppe
  • MR2 Batch job was written to fetch required data from DB and store the same in CSV (static file)
  • Spark job to process the files from Vision EMS and AMN Cache to identify the violations and sending the same to Smarts as SNMP traps.
  • Automated workflows using shell scripting to schedule(crontab) Spark jobs.
  • Exploring with Spark improving the performance and optimization of the existing algorithms in Hadoop using Spark context, Spark-SQL, Data Frame, pair RDD's, Spark YARN.
  • Developed data pipeline using Flume, Sqoop to ingest customer behavioral data and purchase histories into HDFS for analysis.
  • Continuous monitoring and managing the Hadoop cluster using Cloudera Manager.
  • Used Pig to perform data validation on the data ingested using scoop and flume and the cleansed data set is pushed into Hbase.
  • Participated in development/implementation of Cloudera Hadoop environment.
  • Collecting and aggregating large amounts of log data using Apache Flume and staging data in HDFS for further analysis.
  • Worked with Zookeeper, Oozie, and Data Pipeline Operational Services for coordinating the cluster and scheduling workflows.
  • Designed and built the Reporting Application, which uses the Spark SQL to fetch and generate reports on HBase table data.
  • Developed Spark code and Spark-SQL/Streaming for faster testing and processing of data using Lambda Architecture.
  • Experience in deploying data from various sources into HDFS and building reports using Tableau.
  • Developed a data pipeline using Kafka and Strom to store data into HDFS.
  • Performed real time analysis on the incoming data.
  • Re-engineered n-tiered architecture involving technologies like EJB, XML and JAVA into distributed applications.
  • Explored the possibilities of using technologies like JMX for better monitoring of the system.
  • Configured deployed and maintained multi-node Dev and Test Kafka Clusters.
  • Performed transformations, cleaning and filtering on imported data using Hive, Map Reduce, and loaded final data into HDFS.
  • Load the data into Spark RDD and performed in-memory data computation to generate the output response.
  • Loading data into HBase using Bulk Load and Non-bulk load.
  • Created HBase column families to store various data types coming from various sources.
  • Loaded data into the cluster from dynamically generated files
  • Assisted in upgrading, configuration and maintenance of various Hadoop infrastructures
  • Created common audit and error logging processes job monitoring and reporting mechanism
  • Troubleshooting performance issues with ETL/SQL tuning.
  • Developed and maintained the continuous integration and deployment systems using Jenkins, ANT, Akka and MAVEN.
  • Effectively used GIT(version control) to collaborate with the Akka team members.
  • Installed Oozie workflow engine to run multiple Map Reduce, Hive HQL and Pig jobs.
  • Developed HDFS with huge amounts of data using Apache Kafka.
  • Collected the log data from web servers and integrated into HDFS using Flume.

Environment: Spark 1.6.2, Spark Mllib, Spark ML, Hive 1.2.1, Sqoop 1.4.6, Flume 1.5.0, HBase 1.1.4, MySQL 5.6, Scala 2.11.x,Pyspark 1.4.0, AWS, Jenkins.

Confidential, Seattle, WA

Sr. Hadoop Developer

Responsibilities:

  • Involved in all phases of Software Development Life Cycle (SDLC) and Worked on all activities related to the development, implementation and support for Hadoop.
  • Installed and Configured Apache Hadoop clusters for application development and Hadoop tools like Hive, Pig, HBase, Zookeeper and Sqoop.
  • Adding/installation of new components and removal of them through Cloudera Manager
  • Played a key role in installation and configuration of the various Hadoop ecosystem tools such as Solr, Kafka, Pig, HBase and Cassandra.
  • Implemented multiple Map Reduce Jobs in java for data cleansing and pre-processing.
  • Wrote complex Hive queries and UDFs in Java and Python.
  • Involved in creating Spark cluster in HDInsight by create Azure compute resources with spark installed and configured.
  • Involved in implementing an HDInsight version 3.3 clusters, which is based on spark version 1.5.1.
  • Good knowledge in using components that are used in cluster such as spark core (Includes Spark core, Spark SQL, Spark streaming API’s.)
  • Responsible for data extraction and data ingestion from different data sources into Hadoop Data Lake by creating ETL pipelines using Pig, and Hive
  • Installed APACHE NIFI and MINIFI to make data ingestion Fast, Easy and Secure from internet of anything with HORTONWORKS DATA FLOW and Configuring, Managing permissions for the users in hue
  • Worked with systems engineering team to plan and deploy new Hadoop environments and expand existing Hadoop clusters and Experience in converting MapReduce applications to Spark.
  • Job duties involved the design, development of various modules in Hadoop Big Data Platform and processing data using Map Reduce, Hive, Pig, Sqoop and Oozie.
  • Design, developed and tested Map Reduce programs on Mobile Offers Redemptions and Send it to the downstream applications like HAVI. Scheduled this Java map reduce job through Oozie workflow.
  • Ingested huge amount of XML files into Hadoop by Utilizing DOM Parsers with in Map Reduce. Extracted Daily Sales, Hourly Sales and Product Mix of the items sold in McDonalds Restaurant’s and loaded them into Global Data Warehouse.
  • Developed and maintained the continuous integration and deployment systems using Jenkins, ANT, Akka and MAVEN.
  • Effectively used GIT(version control) to collaborate with the Akka team members.
  • Installed Oozie workflow engine to run multiple Map Reduce, Hive HQL and Pig jobs.
  • Developed HDFS with huge amounts of data using Apache Kafka.
  • Collected the log data from web servers and integrated into HDFS using Flume.
  • Created and maintained Technical documentation for launching HADOOP Clusters and for executing Hive queries and Pig Scripts and Experience in managing and reviewing Hadoop log files
  • Constructed System components and developed server side part using Java, EJB, and Spring Frame work. Involved in designing the data model for the system.
  • Used J2EE design patterns like DAO, MODEL, Service Locator, MVC and Business Delegate.
  • Worked with cloud services like Amazon Web Services (AWS) and involved in ETL, Data Integration and Migration
  • Converted all the vap processing from Netezza and implemented by using Spark data frames and RDD's.
  • Installed Oozie workflow engine to run multiple Hive and pig jobs.
  • Analyzed large amounts of data sets to determine optimal way to aggregate and report on it.
  • Involved in converting Hive/SQL queries into Spark transformations using Spark RDD, Scala and Python.
  • Implemented a proof of concept (Poc's) using Kafka, Strom, HBase for processing streaming data.
  • Implemented a script to transmit sysprin information from Oracle to Hbase using Sqoop.
  • Implemented best income logic using Pig scripts and UDFs.
  • Component unit testing using Azure Emulator Analyze escalated incidences within the Azure SQL database.

Environment: Hadoop, Map Reduce, Spark, shark, Kafka, Cloudera, AWS, HDFS, Zoo Keeper, Hive, Pig, Oozie, Core Java, Eclipse, Hbase, Sqoop, Netezza, EMR, Apache NIFI, Flume, Scala, Oracle 11g, Cassandra, SQL, Python, Sharepoint, Azure 2015, GIT, UNIX Shell Scripting, Linux, Jenkins and Maven.

Confidential, Port Washington, NY

Hadoop Developer/Admin

Responsibilities:

  • Working as Hadoop Developer and admin in Hortonworks (HDP 2242) distribution for 10 clusters ranges from POC to PROD
  • Responsible for Cluster maintenance, Monitoring, commissioning and decommissioning Data nodes, Troubleshooting, Manage and review data backups, Manage & review log files
  • Used Spark API over Cloudera Hadoop YARN to perform analytics on data in Hive.
  • Configured, Designed implemented and monitored Kafka cluster and connectors.
  • Hands on experience in writing MR jobs for cleansing the data and to copy it to AWS cluster form our cluster.
  • Experienced on adding/installation of new components and removal of them through Ambari
  • Monitoring systems and services through Ambari dashboard to make the clusters available for the business
  • Architecture design and implementation of deployment, configuration management, backup, and disaster recovery systems and procedures
  • Worked with HQL and Criteria API from retrieving the data elements from database.
  • Hand on experience on cluster up gradation and patch upgrade without any data loss and with proper backup plans
  • Used Sqoop to import data into HDFS from Oracle, MySQL, Netezza and Access databases and vice-versa.
  • Changing the configurations based on the requirements of the users for the better performance of the jobs
  • Experienced in Ambari-alerts configuration for various components and managing the alerts
  • Worked on migrating MapReduce programs into Spark transformations using Scala.
  • Good troubleshooting skills on Hue, which provides GUI for developers/business users for day to day activities
  • Developed MapReduce programs to cleanse the data in HDFS obtained from heterogeneous data sources to make it suitable for ingestion into Hive schema for analysis
  • Implemented 100 node CDH4 Hadoop cluster on Red hat Linux using Cloudera Manager
  • Implemented complex MapReduce programs to perform joins on the Map side using distributed cache
  • Setup flume for different sources to bring the log messages from outside to Hadoop HDFS
  • Implemented Name Node HA in all environments to provide high availability of clusters
  • Working experience on maintaining MySQL databases creation and setting up the users and maintain the backup of cluster metadata databases with Cron jobs
  • Setting up MySQL master and slave replications and helping business applications to maintain their data in MySQL Servers
  • Helping the users in production deployments throughout the process
  • Written Storm topology to accept the events from Kafka producer and emit into Cassandra DB
  • Experienced in production support which involves solving the user incidents varies from sev1 to sev5

Environment: Hadoop, Map Reduce, Cloudera, AWS, HDFS, Pig, Hive, Yarn, HBase, MapReduce, Kafka, Sqoop, Flume, Zookeeper, EMR, Netezza, Hortonworks, Scala, Eclipse, MYSQL, Python, UNIX, Shell Scripting, Jenkins

Confidential, San Mateo, CA

Hadoop Developer

Responsibilities:

  • Responsible to manage data coming from different sources and involved in HDFS maintenance and loading of structured and unstructured data.
  • Developed data pipeline using Flume, Sqoop, Pig and Java MapReduce to ingest behavioural data into HDFS for analysis.
  • Responsible for importing log files from various sources into HDFS using Flume.
  • Imported data using Sqoop to load data from MySQL to HDFS on regular basis.
  • Extracted files from MongoDB through Sqoop and placed in HDFS and processed.
  • Created customized BI tool for manager team that perform Query analytics using Hive QL.
  • Created Partitions, Buckets based on State to further process using Bucket based Hive joins.
  • Estimated the hardware requirements for NameNode and DataNodes & planning the cluster.
  • Developed framework to import the data from database to HDFS using Sqoop. Developed HQLs to extract data from Hive tables for reporting.
  • Hands on experience in writing MR jobs for cleansing the data and to copy it to AWS cluster form our cluster
  • Used open source web scraping framework for python to crawl and extract data from web pages.
  • Possess strong skills in application programming and system programming using C++ and Python on Windows and LINUX platforms using principles of Object Oriented Programming (OOPS) and Design Patterns
  • Moved Relational Database data using Sqoop into Hive Dynamic partition tables using staging tables.
  • Optimizing the Hive queries using Partitioning and Bucketing techniques, for controlling the data distribution.
  • Worked with Kafka for the proof of concept for carrying out log processing on a distributed system. Worked with NoSQL database Hbase to create tables and store data.
  • Worked on custom Pig Loaders and storage classes to work with variety of data formats such as JSON and XML file formats.
  • Involved in Cassandra Data Modelling and Analysis and CQL (Cassandra Query Language).
  • Experience in Upgrading Apache Ambari, CDH and HDP Cluster.
  • Configured and Maintained different topologies in Storm cluster and deployed them on regular basis.
  • Experienced with different kind of compression techniques like LZO, GZip, and Snappy.
  • Used Oozie workflow engine to manage interdependent Hadoop jobs and to automate several types of Hadoop jobs such as Java map-reduce Hive, Pig, and Sqoop.
  • Experience in Upgrading hadoop cluster hbase/zookeeper from CDH3 to CDH4.
  • Involved in Agile SDLC during the development of project.
  • Create a complete processing engine, based on Cloudera's distribution, enhanced to performance.
  • Experienced in Monitoring Cluster using Cloudera manager.

Environment: Hadoop, HDFS, HBase, MapReduce, Java, AWS, JDK 1.5, J2EE 1.4, Struts 1.3, Hive, Pig, Sqoop, Flume, Kafka, Oozie, C++, Hue, Storm, Zookeeper, AVRO Files, Netezza, SQL, ETL, Python, Cassandra, Cloudera Manager, MySQL, MongoDB,Jenkins

Confidential, Moberly, MO

Hadoop Developer

Responsibilities:

  • Worked as Hadoop Developer and responsible for taking care of everything related to the clusters total of 60 nodes ranges from POC to PROD clusters
  • Experienced on setting up Horton works cluster and installing all the ecosystem components through Ambari and manually from command line
  • Responsible for Cluster maintenance, commissioning and decommissioning Data nodes, Cluster Monitoring, Troubleshooting, Manage and review data backups, Manage & review Hadoop log files
  • Load log data into HDFS using Flume, Kafka and performing ETL integrations
  • Experience in Cloudera Hadoop Upgrades and Patches and Installation of Ecosystem Products through Cloudera manager along with Cloudera Manager Upgrade
  • Responsible for Installation of various Hadoop Ecosystems and Hadoop Daemons
  • Working experience on maintaining MySQL databases creation and setting up the users and maintain the backup of databases
  • Implemented Kerberos Security Authentication protocol for existing cluster
  • Involved in transforming data from Mainframe tables to HDFS, and HBASE tables using Sqoop and Pentaho Kettle And also worked on Impala to analyze stored data
  • Have deep and thorough understanding of ETL tools and how they can be applied in a Big Data environment And supporting and managing Hadoop Clusters using Apache, Horton works, Cloudera and MapReduce
  • Involved in loading data from UNIX file system to HDFS And Created custom Solr Query components to enable optimum search matching
  • Involved in writing Map reduce programs and tested using MRUnit
  • Installed and configured local Hadoop Cluster with 3 nodes and set up 4 nodes cluster on EC2 cloud
  • Written MapReduce code to process and parsing the data from various sources and storing parsed data into HBase and Hive using HBase - Hive Integration
  • Developing scripts and batch job to schedule a bundle (group of coordinators), which consists of various Hadoop programs using Oozie
  • Exported the analyzed data to the relational databases using Sqoop for visualization and to generate reports
  • Installed and configured Hadoop MapReduce, HDFS, developed multiple MapReduce jobs in java for data cleaning and pre-processing
  • Installation and Configuration of VMware vSphere client, Virtual Server creation and resource allocation
  • Monitoring Hadoop Cluster through Cloudera Manager and Implementing alerts based on Error messages Providing reports to management on Cluster Usage Metrics

Environment: HDFS, Map Reduce, HBase, Kafka, Yarn, Mongo DB, Hive, Impala, Oozie, Pig, Sqoop, Shell Scripting, MySQLdb, Red Hat Linux, CentOS and other UNIX utilities, Cloudera Manager, Jenkins

Confidential

Java Developer

Responsibilities:

  • Designed a system and developed a framework using J2EE technologies based on MVC architecture .
  • Involved in the iterative/incremental development of project application. Participated in the requirement analysis and design meetings.
  • Designed and Developed UI’s using JSP by following MVC architecture
  • Designed and developed Presentation Tier using Struts framework, JSP, Servlets, TagLibs, HTML and JavaScript.
  • Designed the control which includes Class Diagrams and Sequence Diagrams using VISIO.
  • Used the STRUTS framework in application. Programmed the views using JSP pages with the struts tag library, Model is a combination of EJB’s and Java classes and web implementation controllers are Servlets.
  • Generated XML pages with templates using XSL. Used JSP and Servlets, EJBs on server side.
  • Developed a complete External build process and maintained using ANT.
  • Implemented Home Interface, Remote Interface , and Bean Implementation class .
  • Implemented business logic at server side using Session Bean.
  • Extensive usage of XML - Application configuration, Navigation, Task based configuration.
  • Designed and developed Unit and integration test cases using Junit.
  • Used EJB features effectively- Local interfaces to improve the performance, Abstract persistence schema, CMRs.
  • Used Struts web application framework implementation to build the presentation tier.
  • Wrote PL/ SQLqueries to access data from Oracle database.
  • Set up Web sphere Application server and used ANT tool to build the application and deploy the application in Web sphere .
  • Prepared test plans and writing test cases
  • Implemented JMS for making asynchronous requests

Environment: Java, J2EE, Struts, Hibernate, JSP, Servlets, HTML, CSS, UML, JQuery, Log4J, XML Schema, JUNIT, Tomcat, JavaScript, Oracle 9i, UNIX, Eclipse IDE.

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