SUMMARY

• A Bachelor of Technology (Honors) from Indian Institute of Technology, Kharagpur, India with over 11 years of programming and software architecture, design and development experience with skills in cloud and distributed computing, data storage and analysis, testing and deployment of large scale software systems and applications with keen emphasis on efficiency, elegance, extensibility and scalability.
• 6+ years’ experience with teh tools in teh Hadoop Ecosystem including. Pig, Hive, Impala, Hadoop HDFS, Flume, HBase, Hadoop MapReduce, Sqoop, Flume, Oozie, ZooKeeper and Apache Hue.
• Worked extensively with CDH3, CDH4 and CDH5. Used teh Cloudera Manager and Ambari to administrate, maintain and troubleshoot a cluster.
• Extensive experience with all types of databases from embedded to large scale data lakes including Derby, etcd, SQLite, MySQL, PostgreSQL, Cassandra, HBase, MongoDB and ElasticSearch.
• Hands on experience with installing, configuring, administrating, debugging and troubleshooting Hadoop, ElasticSearch, Kafka, Spark, MySQL and Cassandra clusters.
• Worked across multiple teams to deliver scalable multipurpose technology platforms for company wide initiatives.
• Implemented Apache NiFi processors to move data processing and ETL to teh edge of teh network in order to reduce inefficiencies of data storage and transport and concentrate on just teh data needed for analysis.
• Setup, configured and implemented Nginx webserver using Docker containers for agile devops style deployments.
• Created a custom Docker registry for teh team to collaborate on Docker images using Git SCM.
• Configured a 10 node Hadoop cluster using SequencIQ and OpenStack Heat.
• Keen emphasis on automation in every aspect of teh architecture from infrastructure orchestration to configuration management to application build and deployment.
• Imported teh Apache Mahout machine learning libraries to write advanced data mining and statistical procedures like filtering, clustering and classification to extend teh capabilities of teh MapReduce framework.
• Gathered Java classes and methods, and Pig scripts from Apache Data Fu framework to implement some of teh more complicated statistical procedures like quantiles, sampling, set and bag operations.
• Extensive experience in JVM Performance tuning including tuning heap size, GCThresholds/Cycles Memory Management etc.
• Extracted data from traditional databases like Teradata, SQL Server and Oracle 9g and SIEBEL into HDFS for processing using teh Hadoop framework and return teh processed results back to those databases for further analysis and reporting.
• Loaded and extracted data from HDFS, wrote HIVE queries and Pig Scripts, defined Oozie workflows and stored and queried data from HBase using Apache Hue, teh interactive web interface for teh Hadoop framework.
• Worked extensively with Cloud based tools like Amazon Redshift to warehouse, maintain and analyze data using traditional business intelligence tools.
• Designed, developed and implemented an encryption/decryption program using AWS KMS’s envelopment encryption framework.
• Deployed VMs in AWS, GCP, Azure, DigitalOcean and OpenStack using Terraform’s (by Hashicorp) providers.
• Configured Linux network bridges, VxLANs and virtual switches/routers.
• Setup and configured Vyos and OpenWRT virtual routers and Open vSwitch virtual switches to take full advantage of datacenter and rack - awareness so that traffic is routed among teh worker nodes in teh most efficient fashion. For e.g. two datanodes/nodemanagers on teh same physical nodes can has extremely high data transfer rates between them.
• Used br-utils packages (brctl) to modify configurations for virtual bridges for docker containers.
• Installed updates and pre-requisites, configured services, formatted and mounted volumes, and changed system parameters (sysctl) using Ansible playbooks
• Used Resilient Distributed Datasets(RDDs) to manipulate data, perform light analytics and create visualizations using teh high performance distributed computing framework of Apache Spark
• Expertise with analyzing, managing and reviewing and troubleshooting problems with Hadoop log files.
• Implemented multiple regressions, hypothesis testing and p-value estimation using R, Python and Scala.
• Implemented teh breeze library for sparse computation is Scala.
• Performed principal component analysis to find out independent relationships between regressors and teh variable being estimated.
• Involved in implementing teh Presto querying engine for ad-hoc analytic queries against data in HDFS and Swift.
• Involved in conducting benchmarks for various SQL frameworks including Spark SQL, Hive, Presto and Drill.
• Configured Swift Proxy Servers to interface with CEPH to provide a scalable object store.
• Configured Apache Sqoop to run SQL queries to import data from databases to HDFS.
• Experience in importing, manipulating and exporting data using Sqoop from HDFS to RDBMS systems like MySQL and SQL Server especially where teh relational data size was hundreds of gigabytes.
• Extensive experience in writing Pig Scripts to analyze, summarize, aggregate, group and partition data.
• Created UDFs to implement functionality not available in Pig. Used UDFs from Piggybank UDF Repository.
• Setup and configured SQL Server 2014 for storing IIS 8 transaction logs and server configurations.
• Performed price comparisons between various cloud platforms to determine teh feasibility of running our application on public cloud vs private cloud.
• Setup Ambari Metrics in embedded mode to collect aggregated metrics for all HDP components onto one large disk.
• Highly experienced in writing HiveQL queries for both managed and external tables. Written multiple UDFs and Stored Procedures for regular maintenance and analysis.
• Extended my skills in HIVE to Apache Impala which copies teh relevant data to main memory (RAM) before running teh query, thus enhancing teh speed of execution by a factor of 100(In-memory data processing). Processed click data to find out response rate of email marketing campaigns using Impala.
• Used Apache Flume to ingest data from various sources like log files and Relational Databases to HDFS using multiple sources and channels and wrote teh data to sinks, one at a time. Managed teh Flume instances across teh project.
• Good understanding of NoSQL Data bases and hands on work experience in writing applications on No SQL databases like Cassandra and Mongo DB.
• Implemented pattern-matching and string search using case classes and regular expressions in Scala.
• Excellent communication skills, interpersonal skills, problem solving skills, and a team player.

TECHNICAL SKILLS

Platform Infrastructure: OpenStack, Ansible, Terraform, Puppet, Chef, Mesos, Marathon, Chronos, Ceph, AWS S3, AWS EC2, AWS KMS, GCP Dataproc, GCP Dataflow

Tools: in teh Hadoop Ecosystem: HDFS, Map Reduce, Hive, Pig, Sqoop, Flume, Oozie, Avro, Datastax Cassandra, Apache Cassandra, Apache YARN, HBase, Zookeeper, Chukwa Cloudera CDH3, CDH4, Apache Whirr, Apache Big Top, Apache Solr, Apache Nutch, Apache Lucene, Apache Sentry, Apache Spark, Spark SQL, Spark MLLib Microsoft HD Insight, Hortonworks Ambari, AWS, Amazon EC2, S3, HiveQL, Pig Latin, Apache Drill, Apache Zeppelin. Google Cloud Container Engine, Kubernetes, Google Cloud Dataproc, Google Cloud Dataflow.

Languages: C/C++, Scala, JavaScript, JAQL, Clojure, Java, R Scripting Language, Python, T-SQL & PL/SQL

Analysis and Reporting Tools: Microsoft SSRS2012/2014, Microsoft SSAS 2014, Splunk, Tableau, Pentaho, Data Mining

Predictive Analytics: R, Stata, SPSS, MATLAB, Machine learning libraries in Mahout and Spark, H2O, Skytree Data Platform

Java Technologies and Frameworks: Struts Framework, Spring, Hibernate, J2EE, JDBC, Multi-threading, JSP, Servlets, JSF, SOAP, XML, XSLT, JSON, Message Pack and DTD. Scala based frameworks like Akka and Play.

Other Technologies: Maven, Microsoft Office, Ubuntu, RedHat Linux(RHEL), OpenStack Cloud Computing Framework, Jenkins GitHub, PLSQL Developer, Log4J, CVS. Git Stash and IntelliJIDEA.

PROFESSIONAL EXPERIENCE

Confidential, Philadelphia, PA

Big Data Architect

Responsibilities:

• Responsible for design development, test and implementation of a 40 node 10TB Hadoop cluster as a datastore for storing and providing access to 50+ customer event datasets. 3 such clusters were built for DR purposes and read access was provided through VIPs on each DC fronted by a GSLB.
• Setup and configured HTTPS on teh Customer Timeline UI with SSL certificates issued by COMODO and integrated with companywide AD and Kerberos autantication systems.
• Gathered requirements from 20+ teams including teh amount of data, teh kind of data, frequency of generation, ageing policy and sensitivity of data w.r.t. extant company policy.
• Involved in rationalizing teh various data sources and creating a streamlined, scalable and extensible process to ingest a variety of data sources based on a standardized schema and configuration variables.
• Involved in modeling, creating and updating teh schema for HBase to ingest teh data.
• Setup, configured and tuned Apache NiFi to collect data from teh edge, transform it to meet schema requirements, and finally ingest into teh HBase.
• Configured and tuned NiFi w.r.t. number of threads, number of parallel processors, disk throughput and security (Access control and authorization).
• Conducted performance tests on various combinations of RAM and CPU to determine optimal instance sizing for various components.
• Wrote bash and Python scripts to provision and pre-configure OpenStack Nova instances and Cinder volumes for HDP install.
• Set up REST gateways to enable HTTP based access to teh data.
• Wrote Python scripts to automate teh performance testing/benchmarking for teh Read API using teh Locust framework.
• Setup and configured topics with replication and partitions to store customer event data in Apache Kafka.
• Tuned Kafka’s settings including message buffer size, timeout and retries to ensure that teh message broker performed reliably and with low latency even with sudden spikes in data.
• Set up and configured Kafka Mirror Maker to enable synchronization between enterprise and satellite Kafka.
• Configured Kafka log-retention based on size of topic on disk to ensure maximum utilization of available disk.
• Planned and implemented a 5 node ElasticSearch cluster with a Kibana dashboard to record metrics for ingestion data.
• Planned and implemented active-active replication across 3 physical datacenters and seamless failover to ensure that teh application is highly available.
• Designed and implemented a MySQL distributed cluster of 10 nodes for analytic use cases (It is very inefficient to make queries conditioned on non-row keys to HBase).
• Developed, tested and deployed an AWS Key Management System based encryption solution in Java to encrypt PII/PCI data and warehouse it to comply with company security policy.
• Setup and configured a master build server with Maven and Jenkins for DM/CI and integrated it to GitHub Enterprise to enable automatic build on commit.
• Wrote RFPs and performed teh vendor evaluation/selection process for hiring a 12 member offshore operations team to provide 24/7 operations support for both Customer Timeline and Smart Connect.
• Co-ordinated onboarding of teh team, familiarizing them with teh platform, training them to take over our infrastructure and applications. Worked with various SMEs in Confidential to ensure that all teh relevant information is available to and understood by teh offshore ops team.
• Handed off infrastructure to relevant operational support teams.
• Setup and configured IIS 8 webservers behind a VIP and GSLB and helped deploy a .NET webAPI
• Setup and implemented a 5 node Consul cluster for controlling datacenter and prod/soak enable/disable for webAPI.
• Created, configured and implemented a 3 node FluentD cluster for collecting real-time events and buffering them for ingest into ElasticSearch.
• Setup, configured and deployed four 10 node ElasticSearch clusters and created indexes for ingesting real-time customer event data.
• Used Java NIO libraries to write asynchronous code based on Futures and Callbacks to enable real-time ingest of customer event data.
• Used Apache Flink 0.9.0 for a streaming analytics POC to stream data from a Kafka topic, filter it by status code, aggregate it by time and store teh output in an Avro file on HDFS.
• Setup and configured GossipingPropertyFileSnitch on a 6 node Cassandra cluster with 2 DCs where NetworkTopologyStrategy was used with varying replications to different workloads.
• Designed and validated a CQL data model with 2 tables and 3 views to ingest WebAPI logs into Cassandra and view metrics about them on a Grafana dashboard and created Materialized Views to query non-primary key columns.
• Was responsible teh design, implementation, benchmarking and operational ownership for three clusters 50,120 and 183 nodes with 4 TB, 30 TB and 340TB of effective HDFS storage.
• Extensively used devops automation tools like Terraform and Ansible to orchestrate and configure VMs for HDP install.
• Conducted a POC to integrate teh Ambari and OpenStack REST APIs to enable one click deploys of Hadoop clusters.
• Planned and implemented processes for periodic ingest of infrastructure telemetry into Swift, OpenStack object store. Teh data in approx. 2 TB per day of CDN logs, IP video logs and CDR logs.
• Involved in capacity planning, hardware estimation and allocation for teh various big data initiatives.
• Installed, and configured Hortonworks Data Platform 2.2.x, 2.3.x and 2.4.x on teh three clusters respectively.
• Performed express upgrade of teh 120 node cluster from HDP 2.2.6.0 to HDP 2.3.4.0 in one day.
• Designed, architected and built a 30 node cluster with all ephemeral disks to ensure node locality for data-science workloads where there is a large amount of iterative processing and high me/O.
• Integrated OpenStack Swift into HDP to enable querying of Swift containers using Hadoop clients and running MapReduce/Spark jobs against them.
• Developed Scala code leveraging Spark SQL to execute JOINs and aggregations on raw logs of up to 3 months of data.
• Created encryption zones for certain directories to store sensitive data on HDFS. It gets transparently encrypted and decrypted as it is written and read.
• Configured special high bandwidth, high IOPS SolidFire disks for Hadoop components like Namenodes, Zookeepers, JournalNodes and Kafka broker disks.
• Setup and configured Flafka (Flume and Kafka) to read from a topic as messages came through and ingest them into HDFS in Avro format.
• Implemented FairScheduler with pre-emption on YARN to accommodate for varying workload with creating quotas based inefficiencies.
• Configured encrypted shuffle/sort in Hadoop using Kerberos to store SSL keys.
• Developed Python and Shell scripts to perform aggregations on simulation outputs.
• On boarded new users for teh clusters including providing them new users, helping them understand teh cluster and its capacity and ensuring that teh given use case was teh right fit for teh cluster.
• Tuned Linux kernel properties including swap, file descriptors, TCP timeouts/buffers and XFS block sizes to improve performance of cluster.
• Tuned Spark and MapReduce jobs w.r.t. container memory utilization, input file sizes, compression, intermediate data placement and compression, and writing of final output to HDFS/Swift.
• Implemented and productionized teh Swift S3 API so that AWS CLI, Java and Python clients can be used to work with Swift containers.
• Integrated periodic Hadoop jobs with Swift’s auth tokens so that a large number of files can be accessed without making one call per file to teh Keystone auth endpoint.
• Used teh performance numbers from an ensemble of workloads to re-design teh sizes of VMs to rectify shortfalls in memory and CPU.
• Installed and deployed H20 machine learning framework on teh Hadoop cluster.
• Installed and configured RStudio in teh same environment to ensure that R jobs could be run on Spark that was available on teh cluster.
• Setup cron jobs to rebalance teh cluster once a week to ensure evenly distributed data.
• Trained and transferred ownership of teh cluster to teh operations team.
• Conducted a POC on using Netty ByteBuf and async channels to improve me/O performance for encrypting and enriching IP telemetry.
• Setup and configured Tachyon, an in-memory filesystem with both HDFS and Swift as underFSes to realize a tiered-storage architecture for SLA based self-service analytics.
• Setup processes in NiFi for converting JSON data into Avro and ingesting teh same into HBase, Cassandra and ElasticSearch.
• Used R and Scala’s MLLib to forecast cloud infrastructure demand using Multivariate Linear Regression and logistic regression. Amount of data per team, growth rate of data and ageing policies (in number of days) were teh independent variables.

Environment: Hortonworks Data Platform 2.2.x, 2.3.x, 2.4.x, Cloudera Manager, Cloudera Director, Apache Hadoop 2.7.1, Spark 1.6.0, Scala 2.11, Flink, Avro, H2O, Ambari 2.2.1, Terraform, Ansible 2.0, Consul, Zookeeper, cloud-init, Bash, Python 2&3, Java 8, Hive, Pig, HBase, Cassandra, ElasticSearch, SQLite, MySQL.

Confidential, New York, NY

Sr. Cassandra Developer/Administrator

Responsibilities:

• Responsible for building scalable distributed data solutions using Datastax Cassandra.
• Involved in business requirement gathering and proof of concept creation.
• Created data models in CQL for customer data.
• Involved in Hardware installation and capacity planning for cluster setup.
• Involved in teh hardware decisions like CPU, RAM and disk types and quantities.
• Used teh Spark - Cassandra Connector to load data to and from Cassandra.
• Setup and configured nginx as a reverse proxy to ingest data from external sources into Cassandra through teh custom designed web service.
• Worked with teh Data architect and teh Linux admin team to set up, configure, initialize and troubleshoot an experimental cluster of 12 nodes with 3 TB of RAM and 60 TB of disk space.
• Ran many performance tests using teh Cassandra-stress tool in order to measure and improve teh read and write performance of teh cluster.
• Wrote Java code to query Cassandra using both teh QueryBuilder API and teh PreparedStatements API.
• Wrote and modified YAML scripts to set teh configuration properties like node addresses, replication factors, client storage space, memTable size and flush times etc.
• Used teh Datastax Opscenter for maintenance operations and Keyspace and table management.
• Loaded and transformed large sets of structured, semi structured and unstructured data in various formats like text, zip, XML, YAML and JSON.
• Created data-models for customer data using teh Cassandra Query Language.
• Used collections like lists, sets and maps to create data models highly optimized for reads and writes.
• Created User defined types to store specialized data structures in Cassandra.
• Developed PIG UDFs for manipulating teh data and extracting useful information according to Business Requirements and implemented them using teh Datastax Pig functionality.
• Responsible for creating Hive tables based on business requirements
• Implemented advanced procedures like text analytics and processing using teh in-memory computing capabilities like Spark.
• Used Scala case classes to implement pattern matching using Regular expressions.
• Enhanced and optimized production Spark code to aggregate, group and run data mining tasks using teh Spark framework.
• Implemented teh clustering algorithms in Mahout to cluster consumer by location of purchase and general category of purchase in order to create specialized and targeted credit and foreign exchange products.
• Implemented a distributed messaging queue to integrate with Cassandra using Apache Kafka and ZooKeeper.
• Used R and RStudio to run various statistical procedures on both time-series and cross-sectional data like regression, density estimation, polynomial estimation, smoothing splines and hypothesis testing.
• Involved in a POC to implement a failsafe distributed data storage and computation system using Apache YARN.
• Used Clojure scripting in web development for real-time dashboards.
• Involved in teh implementation of a POC using teh OpenStack Cloud Computing Framework.
• Tuned and recorded performance of Cassandra clusters by altering teh JVM parameters like - Xmx and - Xms. Changed garbage collection cycles to place them in tune with backups/compactions so as to mitigate disk contention.
• Queried and analyzed data from Datastax Cassandra for quick searching, sorting and grouping.
• Implemented Partitioning, Dynamic Partitions and Buckets in HIVE for efficient data access.
• Participated in NoSQL database integration and implementation.
• Exported teh analyzed data into relational databases using Sqoop for visualization and to generate reports.
• Gathered teh business requirements from teh Business Partners and Subject Matter Experts like Data Scientists.

Environment: Apache Hadoop 2.2.0, Cloudera 4.5, HDP 1.3, Apache Kafka, Cassandra, MapReduce, Spark, Hive 0.12, Pig 0.11, HBase, Linux, XML.

Confidential - Round Rock, Texas

Hadoop Engineer/Developer

Responsibilities:

• Configured teh Hadoop Cluster in Local (Standalone), Pseudo Distributed, Fully Distributed Mode
• Responsible for building scalable distributed data solutions using Hadoop.
• Imported data using Sqoop to load data from MySQL to HDFS on regular basis from various sources.
• Wrote HIVE queries for aggregating teh data and extracting useful information sorted by volume and grouped by vendor and product.
• Worked closely with teh functional team to gather and understand business requirements determine feasibility to and to convert them to technical tasks in teh Design Documents.
• Worked closely with business team to gather requirements and add new support features.
• Implemented Partitioning, Dynamic Partitions and Buckets in HIVE for more efficient data access.
• Involved in NoSQL (Datastax Cassandra) database design, integration and implementation.
• Wrote queries to create, alter, insert and delete elements from lists, sets and maps in Datastax Cassandra.
• Created indices for conditioned search in Datastax Cassandra.
• Implemented Custom JOINS to create tables containing teh records of Items or vendors blacklisted for defaulting payments suing Spark SQL.
• Created use cases and test cases for each of teh queries before shipping teh final production code to teh validation of support and maintenance team.
• Involved in creating a POC for light analytics using Clojure scripts.
• Wrote and implemented Hadoop MapReduce programs in Ruby using Hadoop Streaming.
• Exported teh analyzed data into Teradata using Sqoop for visualization and to generate reports to be further processed by business intelligence tools.
• Wrote a technical paper and created slideshow outlining teh project and showing how Cassandra can be potentially used to improve performance.
• Used teh machine learning libraries of Mahout to perform advanced statistical procedures like clustering and classification to determine teh probability of payment default.
• Ran teh logistic regression in Python and Scala using teh in-memory distributed computing framework of Apache Spark.
• Weekly meetings with technical collaborators and active participation in code review sessions with senior and junior developers.

Environment: Apache Hadoop 2.3.0, Hive 0.12, Horton Works Data Platform, Teradata, Mahout, Cassandra, Ubuntu

Confidential, East Hartford, CT

Hadoop Developer

Responsibilities:

• Installed and configured Apache Hadoop to test teh maintenance of log files in Hadoop cluster.
• Installed and configured Hive, Pig, Sqoop, and Oozie on teh Hadoop cluster.
• Installed Oozie Workflow engine to run multiple Hive and Pig Jobs.
• Setup and benchmarked Hadoop/HBase clusters for internal use.
• Extracted data from databases like SQL Server and Oracle 9g into HDFS for processing using Pig and Hive.
• Performed optimization on Pig scripts and Hive queries increase efficiency and add new features to existing code.
• Performed statistical analysis using Splunk.
• Developed Java MapReduce programs for teh analysis of sample log file stored in cluster.
• Developed Simple to complex Map/Reduce Jobs using Hive and Pig.
• Developed Map Reduce Programs for data analysis and data cleaning.
• Stored and retrieved data from data-warehouses using Amazon Redshift.
• Developed PIG Latin scripts for teh analysis of semi structured data.
• Used Hive and created Hive tables and involved in data loading and writing Hive UDFs.
• Used Sqoop to import data into HDFS and Hive from other data systems.
• Generated aggregations and groups and visualizations using Tableau.
• Continuous monitoring and managing teh Hadoop cluster using Cloudera Manager.
• Migration of ETL processes from Oracle to Hive to test teh easy data manipulation.
• Conducted some unit testing for teh development team within teh sandbox environment.
• Developed Hive queries to process teh data for visualizing and reporting.

Environment: Apache Hadoop, Cloudera Manager, CDH2, CDH3 CentOS, Java, MapReduce, Apache Hama, Eclipse Indigo, Hive, Sqoop, Oozie and SQL.

Confidential

Sr. Software Test Engineer

Responsibilities:

• Tested web based Project Management Application designed to facilitate monitoring different project activities such as tasks, contacts, project progress, ticketing etc.
• Analyzed System Specifications, designed, developed and executed Test Cases
• Performed Extensive Manual Testing for all teh functionalities in teh application
• Involved in various types of process evaluations during each phase of teh software development life cycle including, review, walk through and hands-on system testing
• Performed task allocation and prepared Traceability Matrix for Test Case Status, Peer Review Sheets,
• Bug Tacking Report, and Status update
• Executed test cases and submitted bugs and tracked those using teh Test Director

Environment: Windows 98/2000/XP, PHP, SQL server 2000, Internet Explorer, Mozilla Firefox, IIS, MS-Office

Confidential

Java Software Developer

Responsibilities:

• Involved in gathering and analyzing system requirements.
• Designed teh application using Front Controller, Service Controller, MVC, Factory, Data Access Object, and Service Locator.
• Developed teh web application using Struts Framework.
• Developed entire application based on STRUTS framework and configured struts config.xml, web.xml.
• Created tile definitions, struts config files and resource bundles using Struts framework.
• Implemented validation framework for creation of validation.xml and used validationrules.xml.
• Developed Classes in Eclipse for Java using various APIs.
• Designed, developed and deployed necessary stored procedures, Functions, views in Oracle using TOAD.
• Developed JUnit test cases.

Environment: UNIX Shell scripting, Core Java, Struts, Eclipse, J2EE, JBoss Application Server and Oracle, JSP, JavaScript, JDBC, Servlets, Unified Modeling Language, Toad, JUnit.

Confidential 

Java/ J2EE Developer

Responsibilities:

• Involved in System Analysis and Design methodology as well as Object Oriented Design and development using OOA/OOD methodology to capture and model business requirements.
• Proficient in doing Object Oriented Design using UML Rational Rose.
• Created Technical Design Documentation (TDD) based on teh Business Specifications.
• Created JSP pages with Struts Tags and JSTL.
• Developed UI using HTML, JavaScript, CSS and JSP for interactive cross browser functionality and complex user interface.
• Implemented teh web based application following teh MVC II architecture using Struts framework.
• Used XML DOM API for parsing XML.
• Developed Scripts for automation of productions tasks using Perl, UNIX scripts.
• Used ANT for compilation and building JAR, WAR and EAR files.
• Used JUnit for teh unit testing of various modules.
• Project coordination with other Development teams, System managers and web master and developed good working environment.

Environment: Java, J2EE, JSP, JavaScript, MVC, Servlet, Struts, PL/SQL, XML, UML, JUnit, ANT, Perl, UNIX.