- 10+ Years of experience in Analysis, Design, Development, Enhancement and Implementation of Java, Scala, Akka, Play Framework, AWS, S3, Spark, Hadoop eco - system, HDFS and Elasticsearch based applications.
- 6 Years of experience in Linux and Big data Hadoop, Hadoop Ecosystem components like MapReduce, Sqoop, Flume, Kafka, Pig, Hive, Spark, Storm, HBase, Oozie, and Zookeeper.
- Hands-on experience architecting and implementing Hadoop clusters on Amazon (AWS), using EMR, S2, S3, Redshift, Cassandra, AnangoDB, CosmosDB, SimpleDB, AmazonRDS, DynamoDB, Postgresql., SQL, MS SQL.
- Having good experience in Hadoop framework and related technologies like HDFS, MapReduce, Pig, Hive, HBase, Sqoop and Oozie
- Expert in big data ecosystem using Hadoop, Spark, Kafka with column-oriented big data systems on cloud platforms such as Amazon CLoud (AWS), Microsoft Azure and Google Cloud Platform.
- Expertise in Java, Hadoop Map Reduce, Pig, Hive, Oozie, Sqoop, Flume, Zookeeper, Impala and NoSQL Database and hands of experience on data extraction, transformation and load in Hive, Pig and HBase
- Experienced in performance tuning of Yarn, Spark, and Hive and experienced in developing MapReduce Programs using Apache Hadoop for analyzing the big data as per the requirement.
- Experience in the successful implementation of ETL solution between an OLTP and OLAP database in support of Decision Support Systems with expertise in all phases of SDLC.
- Excellent experience in Amazon, Cloudera and Hortonworks Hadoop distribution and maintaining and optimized AWS infrastructure (EMR EC2, SNS, SQS S3, EBS)
- Exposure to Data Lake Implementation using Apache Spark and developed Data pipe lines and applied business logics using Spark and used Scala and Python to convert Hive/SQL queries into RDD transformations in Apache Spark.
- Expertise in developing Spark code using Scala and Spark-SQL/Streaming for faster testing and processing of data.
- Experienced in Apache Flume for collecting, aggregating and moving huge chunks of data from various sources such as web server, telnet sources etc.
- Extensively designed and executed SQL queries in order to ensure data integrity and consistency at the backend.
- Strong experience in architecting batch style large scale distributed computing applications using tools like Flume, Map reduce, Hive etc.
- Experience using various Hadoop Distributions (Cloudera, Hortonworks, and MapRetc) to fully implement and leverage new Hadoop features.
- Worked on custom Pig Loaders and Storage classes to work with a variety of data formats such as JSON, Compressed CSV, etc.
- Hands-on programming experience in various technologies like JAVA, J2EE, SOAP, HTML, XM
- Excellent Working Knowledge on Sqoop and Flume for Data Processing.
- Expertise in loading the data from the different Data sources like (Teradata and DB2) into HDFS using Sqoop and load into partitioned Hive tables.
- Experienced on Hadoop cluster maintenance including data and metadata backups, file system checks, commissioning and decommissioning nodes and upgrades.
- Extensive experience writing custom Map Reduce programs for data processing and UDFs for both Hive and Pig in Java.
- Extensive experienced in working with structured data using Hive QL, join operations, writing custom UDF's and experienced in optimizing Hive Queries.
- Experienced in importing and exporting data using Sqoop from HDFS to Relational Database and Strong experience in analyzing large amounts of data sets writing Pig scripts and Hive queries.
- Excellent knowledge and experience on Hadoop Architecture and ecosystems such as HDFS, Job Tracker, Task Tracker, Name Node, Data Node, YARN and Map Reduce programming paradigm.
- Experienced working with Hadoop Big Data technologies (hdfs and MapReduce programs), Hadoop echo systems (Hbase, Hive, Vertica, pig) and NoSQL database MongoDB
- Experience with SQL RDBMS like SQL Server, Oracle and My SQL or MPP databases like Vertica, Teradata and Netezza.
- Experienced on usage of No SQL data base column-oriented HBase and BI tools (Spotfire, Crsytal Reports, Lumira, Tableau) integration with Hadoop.
- Extensive experienced in working with semi/unstructured data by implementing complex map reduce programs using design patterns.
- Experienced on major components in Hadoop Ecosystem including Hive, Sqoop, Flume &knowledge of MapReduce/HDFS Framework.
- Hands on experience in using BI tools like Splunk/Hunk, Tableau.
- Experienced in working with different scripting technologies like Python, UNIX shell scripts.
- Strong experienced in working with UNIX/LINUX environments, writing shell scripts and performed analytics in Hive using various files format like JSON, Avro, ORC, and Parquet.
- Working knowledge of database such as Oracle 12c/11g.10g, Microsoft SQL Server, DB2, Netezza.
- Experience in NoSQL databases like HBase, Cassandra, Redis and MongoDB and experience and hands-on knowledge in Akka and LIFT Framework.
- Experience in Object Oriented Analysis, Design (OOAD) and development of software using UML Methodology, good knowledge of J2EE design patterns and Core Java design patterns.
Big Data Technologies: HDFS, YARN, MapReduce, Hive, Pig, Impala, Sqoop, Storm, Flume, Spark, Apache Kafka, Zookeeper, Solr, Ambari, Oozie, MongoDB, Cassandra, Mahout, Puppet, Avro, Parquet, Snappy, Falcon.
NO SQL Databases:: HBase, Cassandra, MongoDB, Amazon DynamoDB, Redis
Hadoop Distributions:: Cloudera (CDH3, CDH4, and CDH5), Hortonworks, MapR and Apache.
Languages: C, C++, Java, Scala, Python, XML, XHTML, HTML, AJAX, CSS, SQL, PL/SQL, Pig Latin, HiveQL, Unix, Java Script, Shell Scripting
Java & J2EE Technologies: Core Java,Hibernate, Spring framework, JSP, Servlets, Java Beans, JDBC, EJB 3.0, Java Sockets & Java Scripts, jQuery, JSF, Prime Faces, SOAP, XSLT and DHTML Messaging Services JMS, MQ Series, MDB, J2EE MVC, Struts 2.1, Spring 3.2, MVC, Spring Web, JUnit, MR-Unit.
Source Code Control:: Github, CVS, SVN, Clearcase
Application Servers:: WebSphere, WebLogic, JBoss, Tomcat
Cloud Computing Tools:: Amazon AWS, (S3, EMR, EC2, Lambda, VPC, Route 53, Cloud Watch, Cloud Front), Microsoft Azure
Databases: Teradata, Oracle 10g/11g, Microsoft SQL Server, MySQL, DB2
DB languages: MySQL, PL/SQL, PostgreSQL & Oracle
Build Tools: Jenkins, Maven, ANT, Log4j
Business Intelligence Tools: Tableau, Splunk
Development Tools: Eclipse, IntelliJ, Microsoft SQL Studio, Toad, NetBeans
ETL Tools: Talend, Pentaho, Informatica, Ab Initio
Development Methodologies:: Agile, Scrum, Waterfall, V model, Spiral
Sr. Bigdata Architect
Confidential, Minneapolis, MN
- Gathered the business requirements from the Business Partners and Subject Matter Experts and involved in installation and configuration of Hadoop Ecosystem components with Hadoop Admin.
- Working on architected solutions that process massive amounts of data on corporate and AWS cloud based servers.
- Involved in the high-level design of the Hadoop architecture for the existing data structure and Business process and involved in analyzing business requirements and prepared detailed specifications that follow project guidelines required for project development.
- Involved in Architecting the Hadoop cluster in Pseudo distributed Mode working with Zookeeper and Apache and storing and loading the data from HDFS to AmazonAWSS3 and backing up and Created tables in AWS cluster with S3 storage.
- Part of Configuring & deployment of Hadoop Cluster in the AWS cloud and worked with clients to better understand their reporting and dash boarding needs and present solutions using structured + Agile project methodology approach.
- Responsible for building scalable distributed data solutions using Apache Hadoop and Spark and developed Spark scripts by using Scala IDEas per the business requirement.
- Collected the JSON data from HTTP Source and developed Spark APIs that helps to do inserts and updates in Hive tables.
- Developed Spark scripts to import large files from Amazon S3 buckets and imported the data from different sources like HDFS/HBase into SparkRDD.
- Used Spark-Streaming APIs to perform necessary transformations and actions on the fly for building the common learner data model which gets the data from Kinesis in near real time and Persists into Cassandra.
- Developed pyspark, scala code to cleanse and perform ETL on the data in data pipeline in different stages
- Built machine learning models to identify whether a user is legitimate using real-time data analysis and prevent fraudulent transactions using the history of customer transactions with supervised learning.
- Involved in making changes in spark API when migrating from spark 1.6 to spark 2.2.0 and used Spark API over Cloudera Hadoop YARN to perform analytics on data in Hive.
- Created Hive queries that helped market analysts spot emerging trends by comparing fresh data with EDW reference tables and historical metrics and developed pig scripts, python to perform Streaming and created tables on the top of it using hive.
- Worked on Amazon Web Services (AWS) services like EC2, S3, and EBS, RDS and VPC and deployed micro-services as restful Java Web Services on Amazon Elastic Beanstalk. Used Amazon S3 for configuration files.
- Handled importing data from different data sources into HDFS using Sqoop and performing transformations using Hive and then loading data into HDFS.
- Built and maintained scalable data pipelines using the Hadoop ecosystem and other open source components like Hive and HBase.
- Implemented Python scripts to import/export JSON file, which contains the customer survey information and/or asset information, to/from the database and used Python for pattern matching in build logs to format errors and warnings
- Closely worked with data science team in building Spark MLlib applications to build various predictive models and worked extensively on spark and MLlib to develop a regression model for logistic information.
- Developed Solr web apps to query and visualize and solr indexed data from HDFS and created Partitions, Buckets based on State to further process using Bucket based Hive joins.
- Captured data from existing databases that provide SQL interfaces using Sqoop and implemented Sqooping from Oracle to Hadoop and load back in parquet format.
- Implemented Kafka consumers to move data from Kafka partitions into Cassandra for near real-time analysis and worked extensively on Hive to create, alter and drop tables and involved in writing hive queries.
- Designed columnar families in Cassandra and Ingested data from RDBMS, performed data transformations, and then exported the transformed data to Cassandra as per the business requirement.
- Developed Spark scripts by using Python shell commands as per the requirement and used DataStax Spark-Cassandra connector to load data into Cassandra and used CQL to analyze data from Cassandra tables for quick searching, sorting and grouping.
- Used Jira for bug tracking and Bit Bucket to check-in and checkout code changes and worked with SCRUM team in delivering agreed user stories on time for every Sprint.
- Wrote ETL jobs to read from web APIs using REST and HTTP calls and loaded into HDFS using java and Talend and actively involved in code review and bug fixing for improving the performance and extensively used ETL methodology for supporting Data Extraction, transformations and loading processing, using Hadoop
- Ingested data from RDBMS and performed data transformations, and then export the transformed data to Cassandra as per the business requirement and also used Cassandra through Java services.
Environment: Spark, Spark-Streaming, Kafka, Spark SQL, AWS EMR, HDFS, Hive, Apache Kafka, Sqoop, Java (JDK SE 6, 7), Scala, Shell scripting, Linux, MySQL Oracle Enterprise DB, SOLR, Jenkins, Eclipse, Oracle, BitBucket, Oozie, MySQL, Soap, Cassandra and Agile Methodologies, Scala, Python, AWS S3, AWS EC2, AWS Redshift, Talend, Splunk, Spark MLlib, Java, Hive-QL.
Sr. Bigdata Architect
Confidential, Houston, TX
- Collaborate in identifying the current problems, constraints and root causes with data sets to identify the descriptive and predictive solution with support of the Hadoop HDFS, MapReduce, Pig, Hive, and Hbase and further to develop reports in Tableau.
- Developed Spark Applications by using Scala, Java and Implemented Apache Spark data processing project to handle data from various RDBMS and Streaming sources.
- Worked with the Spark for improving performance and optimization of the existing algorithms in Hadoop using Spark Context, Spark-SQL, Spark MLlib, Data Frame, Pair RDD's, Spark YARN.
- Used Spark Streaming APIs to perform transformations and actions on the fly for building common learner data model which gets the data from Kafka in Near real time and persist it to Cassandra.
- Developed Kafka consumer's API in Scala for consuming data from Kafka topics and consumed XML messages using Kafka and processed the xml file using Spark Streaming to capture UI updates.
- Developed Preprocessing job using Spark Data frames to flatten JSON documents to flat file and load D-Stream data into Spark RDD and do in memory data Computation to generate Output response.
- Integrated Apache Storm with Kafka to perform web analytics. Uploaded click stream data from Kafka to Hdfs, Hbase and Hive by integrating with Storm
- Worked on Amazon Web Services (AWS) cloud services to do machine learning on big data and developed Spark Python modules for machine learning & predictive analytics in Hadoop and implemented a Python-based distributed random forest via PySpark and MLlib.
- Involved in writing live Real-time Processing and core job susing Spark Streaming with Kafka as a data pipe-line system and involved in loading data from rest endpoints to Kafka Producers and transferring the data to Kafka Brokers.
- Creating Hive tables to import large data sets from various relational databases using Sqoop and export the analyzed data back for visualization and report generation by the BI team
- Involvement in creating custom UDFs for Pig and Hive to consolidate strategies and usefulness of Python into Pig Latin and HQL (HiveQL) and scheduled several time based Oozie workflow by developing Python scripts.
- Worked and learned a great deal from AWS Cloud services like EC2, S3, EBS, RDS and VPC and migrated an existing on-premises application to AWS. Used AWS services like EC2 and S3 for small data sets processing and storage, Involved in Maintaining the Hadoop cluster on AWS EMR.
- Imported data from AWS S3into Spark RDD, Performed transformations and actions on RDD's.
- Implemented Elastic Search on Hive data warehouse platform and worked with ELASTIC MAPREDUCE and setup Hadoop environment in AWS EC2 Instances.
- Worked on Cassandra architecture, replication strategy, gossip, snitchetc and used the SparkDataStax Cassandra Connector to load data to and from Cassandra.
- Involved in creating data-models for Client's transactional logs, analyzed the data from Casandra tables for quick searching, sorting and grouping using the Cassandra Query Language (CQL).
- Tested the cluster Performance using Cassandra-stress tool to measure and improve the Read/Writes.
- Used Hive QL to analyze the partitioned and bucketed data, Executed Hive queries on Parquet tables stored in Hive to perform data analysis to meet the business specification logic.
- Used Kafka functionalities like distribution, partition, replicated commit log service for messaging systems by maintaining feeds
- Used Apache Kafka to aggregate web log data from multiple servers and make them available in downstream systems for Data analysis and engineering type of roles.
- Involved in using Avro, Parquet, RCFileand JSON file formats, developed UDFs in Hive and Pig and worked on Cloudera Hue to import data on to the Graphical User Interface.
- Performed transformations like event joins, filter bot traffic and some pre-aggregations using PIG and Worked with Log4j framework for logging debug, info & error data.
- Developed Custom Pig UDFs in Java and used UDFs from PiggyBankfor sorting and preparing the data
- Developed Custom Loaders and Storage Classes in PIG to work on several data formats like JSON, XML, CSV and generated Bags for processing using pig etc.
- Implemented ETL standards utilizing proven data processing patterns with open source standard tools like Talend and Informatica for more efficient processing.
- Worked on Data Warehousing ETL concepts using Informatica Power Center, OLAP, OLTP and AutoSys
- Used Amazon DynamoDB to gather and track the event based metrics and developed Sqoop and Kafka Jobs to load data from RDBMS, External Systems into HDFS and HIVE.
- Developed Oozie coordinators to schedule Pig and Hive scripts to create Data pipelines and written several Map reduce Jobs using Java API, also used Jenkins for Continuous integration.
- Setting up and worked on Kerberos authentication principals to establish secure network communication on cluster and testing of HDFS, Hive, Pig and MapReduce to access cluster for new users.
- Continuous monitoring and managing the Hadoop cluster through Cloudera Manager and modified ANT Scripts to build the JAR's, Class files, WARfiles and EAR files.
- Generated various kinds of reports using Power BI and Tableau based on Client specification and worked with Network, Database, Application, QAand BI teams to ensure data quality and availability.
- Responsible for generating actionable insights from complex data to drive real business results for various applications teams and worked in Agile Methodology projects extensively.
Environment: Spark, Spark-Streaming, Spark SQL, AWS EMR, AWS S3, AWS EC2, MapR, HDFS, Hive, Pig, Apache Kafka, Sqoop, Java (JDK SE 6, 7), Scala, Shell scripting, Linux, MySQL Oracle Enterprise DB, SOLR, Jenkins, Eclipse, Oracle, Git, Oozie, Tableau, MySQL, Soap, NIFI, Cassandraand Agile Methodologies.
Sr. Hadoop Developer/Engineer
- Involved in review of functional and non-functional requirements and involved in upgrading Cloudera hadoop cluster from 5.3.8 to 5.8.0 and 5.8.0 to 5.8.2.
- Worked on all hadoop ecosystems (HDFS, YARN, Map Reduce, Hive, Spark, Flume, Oozie, Zookeeper, Spark, Impala, HBase and Sqoop) through Cloudera manager.
- Worked on migrating MapReduce programs into Spark transformations using Spark and Scala, initially done using python (PySpark).
- Developed Spark jobs using Scala on top of Yarn/MRv2 for interactive and Batch Analysis and involved in querying data using SparkSQL on top of Spark engine for faster data sets processing and worked on implementing Spark Framework, a Java based Web Frame work.
- Worked with Apache SOLR to implement indexing and wrote Custom SOLR query segments to optimize the search and written java code to format XML documents, uploaded them to Solr server for indexing.
- Worked on Apache Solr for indexing and load balanced querying to search for specific data in larger datasets and implemented Near Real Time Solr index on Hbase and HDFS.
- Worked on Ad hoc queries, Indexing, Replication, Load balancing, and Aggregation in MongoDB.
- Processed the Web server logs by developing Multi-hop flume agents by using Avro Sink and loaded into MongoDB for further analysis, also extracted files from MongoDB through Flume and processed.
- Expert knowledge on MongoDB NoSQL data modeling, tuning, and disaster recovery backup used it for distributed storage and processing using CRUD.
- Extracted and restructured the data into MongoDB using import and export command line utility tool.
- Experience in setting up Fan-out workflow in flume to design v shaped architecture to take data from many sources and ingest into single sink.
- Build servers using AWS: Importing volumes, launching EC2, creating security groups, auto-scaling, load balancers, Route 53, SES, SQS and SNS in the defined virtual private connection.
- Involved in working with different join patterns and implemented both Map and Reduce Side Joins.
- Imported several transactional logs from web servers with Flume to ingest the data into HDFS. Using Flume and Spool directory for loading the data from local system(LFS) to HDFS and wrote Flume configuration files for importing streaming log data into HBase with Flume.
- Installed and configured pig, written Pig Latin scripts to convert the data from Text file to Avro format and created Partitioned Hive tables and worked on them using HiveQL.
- Loading Data into HBase using Bulk Load and Non-bulk load and installed, Configured TalendETL on single and multi-server environments.
- Worked in monitoring Hadoop cluster using Cloudera Manager, interacting with Cloudera support and log the issues in Cloudera portal and fixing them as per the recommendations and involved in Cloudera Hadoop Upgrades and Patches and Installation of Ecosystem Products through Cloudera manager along with Cloudera Manager Upgrade.
- Worked on continuous Integration tools Jenkins and automated jar files at end of day.
- Worked with Tableau and Integrated Hive, Tableau Desktop reports and published to Tableau Server.
- Developed data pipeline expending Pig and Java MapReduce to consume customer behavioral data and financial antiquities into HDFS for analysis and developed REST APIs using Java, Play framework and Akka.
- Developed MapReduce programs in Java for parsing the raw data and populating staging Tables and developed Unix shell scripts to load large number of files into HDFS from Linux File System.
- Experience in setting up the whole app stack, setup and debug log stash to send Apache logs to AWS Elastic search.
- Collaborated with Database, Network, application and BI teams to ensure data quality and availability and used Impala connectivity from the User Interface (UI) and query the results using ImpalaQL.
- Used Zookeeper to coordinate the servers in clusters and to maintain the data consistency.
- Worked in Agile development environment having KANBAN methodology. Actively involved in daily Scrum and other design related meetings.
- Used OOZIE Operational Services for batch processing and scheduling workflows dynamically.
- Implementing Hadoop with the AWS EC2 system using a few instances in gathering and analyzing data log files.
- Developed Spark code by using Scala and Spark-SQL for faster processing and testing and performed complex HiveQL queries on Hive tables.
- Supported in setting up QA environment and updating configurations for implementing scripts with Pig, Hive and Sqoop.
- Experienced in using agile approaches including Test-Driven Development, Extreme Programming, and Agile Scrum.
Environment: Hadoop, HDFS, Hive, Map Reduce, AWS EC2, AWS Elasticsearch, AWS S3, SOLR, Impala, MySQL, Oracle, Sqoop, Kafka, Spark, Scala, SQL Talend, Python, PySpark, Yarn, Pig, Oozie, SBT, Akka, Linux-Ubuntu, Scala, Ab Initio, Tableau, Maven, Jenkins, Java (JDK 1.6), Cloudera, JUnit, agile methodologies
- Experienced in migrating and transforming of large sets of Structured, semi structured and Unstructured RAW data from HBase through Sqoop and placed in HDFS for further processing.
- Involved in design, development and testing phases of the project and implemented GUI using Html, Jsp, Tiles, Struts Tag Libs, CSS components.
- Extracted data of everyday transaction of customers from DB2 and export to Hive and setup Online analytical processing.
- Written multiple Map Reduce programs in Java for data extraction, transformation and aggregation from multiple file formats including XML, JSON, CSV and other codec file formats
- Written Java program to retrieve data from HDFS and providing it to REST Services and implemented business logic by writing UDFs in Java and used various UDFs from other sources.
- Implemented Sqoop for large data transfers from RDMS to HDFS/HBase/Hive and vice-versa.
- Implemented partitioning, bucketing in Hive for better organization of the data and involved in using HCATALOG to access Hive table metadata from Map Reduce or Pig code
- Created HBase tables, used HBase sinks and loaded data into them to perform analytics using Tableau.
- Installed, configured and maintained Flume, Hive, Pig, Sqoop and Oozie on the Hadoop cluster.
- Created multiple Hive tables, running hive queries in those data, implemented Partitioning, Dynamic Partitioning and Buckets in Hive for efficient data access
- Experienced in running batch processes using Pig Latin Scripts and developed Pig UDFsfor data manipulation according to Business Requirements.
- Hands on experience in developing optimal strategies for distributing the web log data over the cluster, importing and exporting of stored web log data into HDFS and Hive using Scoop.
- Used LDAP for user Authentication and authorization and developed Enterprise Application using SpringMVC, JSP, MySql
- Developed several REST web services which produces both XML and JSON to perform tasks, leveraged by both web and mobile applications.
- Developed Unit test cases for Hadoop M-R jobs and driver classes with MR Testing library and continuously monitored and managed the Hadoop cluster using Cloudera manager and Web UI.
- Designed the logical and physical data model, generated DDL scripts, and wrote DML scripts for Oracle 10g database.
- Managed and scheduled several jobs to run over a time on Hadoop cluster using oozie.
- Integrated Oozie with the rest of the Hadoop stack supporting several types of Hadoop jobs out of the box (such as Map-Reduce, Pig, Hive, and Sqoop) as well as system specific jobs (such as Java programs and shell scripts).
- Involved in the system integration and user acceptance tests successfully and developed front end using JSTL, JSP, HTML, and Java Script
- Used MAVEN for building jar files of MapReduce programs and deployed to cluster.
- Involved in final reporting data using Tableau for testing by connecting to the corresponding Hive tables using Hive ODBC connector.
- Monitored workload, job performance and capacity planning using Cloudera Manager and performed Cluster tasks like adding, removing of nodes without any effect on running jobs.
- Installed Qlik Sense Desktop 2.xand developed applications for users and made reports using Qlik view.
- Followed Agile Methodology for entire project and supported testing teams.
Environment: Apache Hadoop, Java, MapReduce, HDFS, HBase, CentOS 6.4, Unix, REST web Services, ANT 1.6,Elastic Search, Hive, Pig, Oozie, Java (jdk 1.5), JSON, Eclipse, Qlik view, Qlik Sense, Oracle Database, Jenkins, Maven, Sqoop.
- Developing rules based on different state policy using SpringMVC, iBatis ORM, spring web flow, JSP, JSTL, Oracle, MSSQL, SOA, XML, XSD, JSON, AJAX, Log4j
- Involved in various phases of Software Development Life Cycle (SDLC) such as requirements gathering, modeling, analysis, design, development and testing.
- Generated the use case diagrams, Activity diagrams, Class diagrams and Sequence Diagrams in the design phase using Star UML tool.
- Worked on the agile methodology basis in the project and used Maven as build tool and deploying the application.
- Developed the User Interface using spring framework, JQuery and Ajax.
- Used spring framework AOP features and JDBC module features to persist the data to the database for few applications. Also used the Spring IOC feature to get hibernate session factory and resolve other bean dependencies.
- Involved in SSH key hashing and SFTP transfer of files and extensively worked on Apache and Apache libraries for developing custom web services.
- Developed the persistence layer using Hibernate Framework by configuring the mappings in hibernate mapping files and created DAO and PO.
- Developed various Java beans for performance of business processes and effectively involved in Impact analysis and developed test cases using Junit and Test Driven Development.
- Developed application service components and configured beans using Spring IOC, creation of Hibernate mapping files and generation of database schema.
- Created RESTful web services interface to Java-based runtime engine and accounts.
- Done thorough code walk through for the team members to check the functional coverage and coding standards.
- Actively involved in writing SQL using SQL query builder.
- Actively used the defect tracking tool JIRA to create and track the defects during QA phase of the project.
- Used Tortoise SVN to maintain the version of the files and took the responsibility to do the code merges from branch to trunk and creating new branch when new feature implementation starts.
- Used DAO pattern to retrieve the data from database.
- Worked with WebSphere application server that handles various requests from Client.
Environment: Java/J2EE, JSP, XML, Spring Framework, Hibernate, Eclipse(IDE), Micro Services, Java Script, Struts, Tiles, Ant, SQL, PL/SQL, Oracle, Windows, UNIX, Soap, Jasper reports.