SUMMARY:

• Over 14+ years of experience in IT in the areas of Spark, Big Data Architecture, Hadoop, Cloud Computing, Parallel and High Performance Computing, Mobile technologies, Java/J2EE, JavaScript frameworks, and several other open source frameworks.
• 4.5 years of experience in Spark, Hadoop, Big Data, Cloud Computing, NoSQL, and another 2.5 years of experience in Parallel Computing (Big Data) framework MPI (Similar to Hadoop), and published several papers in conferences on my thesis work “Parallel Framework for Large Scale Unstructured Mesh Generation”.
• Certified Apache Spark Developer and AWS certified Solution Architect.
• Worked in various roles such as Senior Solutions Architect, Team Lead, Senior Developer and successfully lead several small and large development teams.
• Expertize in building analytics applications using Spark Core, Spark Streaming, and Spark SQL.
• Expertize in Big Data Hadoop ecosystem like Hive, HiveQL, Pig, Map Reduce, HDFS, YARN, Sqoop, etc.
• Expertize in NoSQL Databases like HBase, MongoDB and DynamoDB.
• Experience in Hadoop Administration, setting up Hadoop Cluster, Cluster Planning, Job Scheduling, Securing Cluster, Backup and Recovery, Hive, and HBase administration.
• Expertise in designing and developing solutions using AWS Cloud Computing products such as Amazon S3, RedShift, EC2, SQS, Cloud Watch, EBS, EMR, IAM, RDS, CloudFront, CloudFormation, SES, OpsWorks, Elastic Beanstalk, Import/Export, Glaciers, etc.
• Performed a detailed evaluation of Big Data technologies as Cloudera, Hortonworks and Amazon Elastic Map Reduce (EMR)
• Good understanding of Data Warehousing environment, ETL tool like Talend, and BI Reporting tools like QlikView, etc.
• Extensive experience in using Parallel Computing (Big Data) framework Message Passing Interface (MPI).
• Developed a Parallel Computing (Big Data) Framework for generating large scale mesh on simulated human skull, brain, lungs, etc. objects to research the impact on these objects during accidents.
• Advised organizations about big data, a big data strategy, the implementation of big data, which technologies best fit the needs of the organization and implemented the selected big data solution.
• Worked with data scientists and helped them extract actionable insights fromhuge amount of data on theHadoopcluster.
• Mentor, consult, collaborate, review and support Engineering teams, data scientists and business users
• Expertise in using Node JS, Ext JS, Ajax, JavaScript, Spring, Hibernate, Seam, JSF, Rich Faces, and Struts frameworks.
• Expertise in designing and developing applications using Java based technologies, such as Java, J2EE, EJB 3/2.x, Servlets, JSP, JDBC, JSTL, SOAP and REST based Web Services using Jersey and Apache Axis.
• Experience working with offshore teams in different geographic locations and time zones.
• A good team player, problem solver, and quick learner with analytical Skills. Ability to perform at high level to meet deadlines, adaptable to ever changing priorities.
• Experience in various industry verticals - Telecommunications, Networking, Financial Services, Engineering & Construction, Healthcare, Retail and Technology.
• Extensive experience in Waterfall and Agile development methodologies. Ability to quickly and effectively, develop key relationships with a range of project participants including executives, directors, managers, vendors, client stakeholders, and developers. Strong conceptual and analytical skills. Excellent verbal, written communication and presentation skills.

TECHNICAL SKILLS:

Spark Technologies: Spark Core, Spark Streaming, Spark SQL, GraphX

Big Data Technologies: Apache Spark, Hive, Pig, Sqoop, Flume, Kafka, ZooKeeper

Hadoop Technologies: Hadoop, HDFS, MapReduce, MRV2, YARN

NoSQL Databases: Cassandra, HBase, DynamoDB, MongoDB

Hadoop Distributions: Cloudera, Amazon Web Services (AWS) EMR, Hortonworks

AWS Core Services: EMR, S3, RedShift, EC2, IAM, SQS, EBS, RDS, Cloud Watch

AWS Other Services: CloudFront, CloudFormation, SES, OpsWorks, Elastic Beanstalk

Parallel Computing: Message Passing Interface (MPI), PVM

Programming Languages: Scala, Java, Python, JavaScript, C, C++, SQL, PL/SQL

JavaScript Frameworks: Node.js, Ext JS, Angular JS, Express JS, Ajax, Ajax4jsf

Java Technologies: JDK 8, JSF, EJB 3.0/2.x, Servlets, JSP, JMS, JDBC

Open Source Frameworks: Seam, Spring, Hibernate, iBATIS, Struts 1.x/2, Rich Faces, JPA

Mobile Technologies: BREW, J2ME, Android

Web Services: REST, Jersey, Axis 1.x, SOAP, WSDL, UDDI

Databases: Oracle, MySQL, SQL Server, DB2, Informix

Servers: JBoss 4.x, WebSphere, Weblogic, Tomcat, Apache

Version Control: GitHub, Subversion, CVS, ClearCase, CM Synergy

Operating Systems: Linux, UNIX, Sun Solaris, Windows

Others: UML, Visio, Sparx Enterprise Architect, Gliffy, Marketo

PROFESSIONAL EXPERIENCE:

Confidential, San Rafael, CA

Marketing Automation Platform

Responsibilities:

• As hands on Confidential, designed, developed and provided technical guidance for Autodesk Data Platform (ADP) and Marketing Automation Platform (MAP) projects.
• Designed and Developed ADP real time data ingestion module using Spark, Scala, Kafka, HBase, Hive, and Attunity Replicate.
• Used Spark Streaming for receiving real time CDC data from Attunity Replicate through Kafka.
• Used Spark RDD functions, transformations, and actions for processing real time data.
• Used Spark SQL to query Hive tables and converted data into parquet format.
• Developed all the Spark programs using Scala. Used Scala collections, traits, higher order and anonymous functions.
• Created views on Hive tables which contains full and incremental data to provide access to real time data.
• As part of initial Marketing Automation Platform (MAP) project, extended Product team implemented Event Based Ingestion (EBI) solution for data ingestion using Flume, Kafka, S3, Docker Containers, Mesos.
• Developed Flume custom handlers to get real time customer entitlement, pelican data from LEM, Pelican applications.
• Received user email activity data from sendwithus and ingested that real time data in S3 from Kafka, Flume custom handlers.
• Implemented a centralized Data Lake in Hadoop with data from various sources.
• Used Sqoop to import various RDBMS table data into Autodesk Data Lake (HDFS) on daily basis.
• Created a shell script to switch hive metastore to point to new tables every night after the merge.
• Fast Access was developed using Amazon Redshift and finally connecting it to Qlikview for Visualizations and reporting.
• Designed a solution for finding complex hierarchies of each and every Autodesk product version history.
• Developed a MapReduce program to find entire hierarchy path of a product upgrade, merges and complex split relationships.
• Stored MapReduce program output in Amazon S3 and developed a script to move the data to RedShift for generating a dashboard using QlikView.
• Presented developed MapReduce solution and designed solutions for other problems in ADP and MAP projects to executive staff, business folks and got approval from them to proceed with Hadoop implementation.
• Designed Subscription Messaging and MailBroker applications to utilize Marketo (marketing automation software) to send emails to Autodesk end customers and vendors.
• Copied Marketo activity data to Amazon S3 (Simple Storage Service) using Sqoop and performed several analytics on Marketo activity data using Hive.
• Provided development team with initial implementation of MailBroker application and showed how to send messages from Amazon SQS (Simple Queue Services), consume and process them to send emails through Marketo using their REST API services.
• Developed and documented on wiki the entire architecture of the Enterprise Data Lake for the Big Data platform at Autodesk.
• Engaging business partners for gathering requirements, conducting workshops and propose various ideas to streamline existing reporting processes. The role also involved project planning and tracking, change management, risk mitigation and deployment strategies during the tenure of the project.

Environment: Apache Spark, Spark Streaming, Scala, Spark SQL, Hadoop, MapReduce, HDFS, Hive, Pig, Sqoop, Flume, Kafka, HBase, Big Data, NoSQL, Qubole, Docker Containers, Mesos, Cleo Harmony, Amazon Web Services, AWS S3, RedShift, EMR, EC2, SQS, Node JS, Dynamo DB, Denodo, Marketo, SendWithUs, SQL Workbench, Data Warehouse, QlikView, GitHub, Sparx Enterprise Architect, Scrum, Agile Methodology.

Hadoop Developer

Confidential

Responsibilities:

• Involved in all phases of the application development such as Requirement Analysis, Design, Development, Deployment, and Testing.
• Analyzed and generated reports based on the previous NS train accidents, repairs, maintenance, etc. data using Apache Hadoop, Pig, and Hive frameworks.
• Developed several Map Reduce programs to extract necessary information from unstructured data provided by ITC messaging and various other systems.
• Pig framework is used to categorize the wayside status, base stations, and subscriptions messages.
• Hive framework is used for generating reports from train accidents, repairs, and maintenance information.
• Wrote several Hive-QL queries to perform the data analysis on the locomotive and base stations data.
• Sqoop is used for transferring big data stored in HDFS to relational databases such as DB2, Oracle, etc and vice versa.
• Worked as a Hadoop Administrator and set up 6 node cluster with core Apache Hadoop distribution.
• Wrote scripts to schedule Hadoop jobs, installed Hive and HBase on the cluster.
• Designed high and low level architectural diagrams for entire PTC application.
• Analyzed all the available NoSQL databases (mainly Cassandra, MongoDB, HBase) to find out which one suits best for several rewriting applications.
• Rewrote time variant systems like NS train route search, goods search, etc using MongoDB NoSQL database.
• Rewrote existing front end web applications using Ext JS JavaScript framework to bring the old applications out of WebLogic portal server.
• Implemented the DAO layer of rewriting applications with MongoDB NoSQL database.
• Implemented sharding, replication on multi node MongoDB database servers.
• Created indexes, aggregation, and have done basic MongoDB monitoring and administration.

Environment: Apache Hadoop, Hive, Sqoop, Big Data, NoSQL, MongoDB, Cassandra, Cloudera, HBase, ZooKeeper, Pig, Sencha Ext JS, Ajax, JavaScript, PVCS, REST, Jersey, Web Services, Ant, HP Service Manager, Linux, Windows.

Senior Solution Architect

Confidential

Responsibilities:

• Redesigned DNCS Confidential branding application using Struts 2, Spring, Hibernate, and RESTful web services.
• Created architectural, data model, and various types of UML diagrams using Sparx Enterprise Architect software.
• Developed all the UI pages in network, system provisioning, app server modules using Struts 2 MVC framework.
• Used Spring framework for Dependency Injection and integrated with Struts 2 and Hibernate frameworks.
• Implemented DAO layer using Hibernate and used Spring implementation of HibernateDAOSupport for data persistence.
• Created hibernate mapping files and developed POJO’s to map objects to relational database tables.
• Designed and developed RESTful Web Services to get Generic QAM and QPSK information from database.
• Enterprise Architect/Lead Developer - Cox Communications, Atlanta, GA (Sep 07 - May 10)
• Projects: eCommerce, eMergence, Contracts & Developments Admin Portal, PinTools
• Played different roles such as Solution Architect, Team Lead, and Scrum Master.
• Designed eCommerce, eMergence, Contracts & Developments Admin Portal, PinTools applications using JBoss Seam, JSF, EJB3, Facelets, Ajax4JSF, RichFaces, and Interwoven Teamsite CMS.
• Created architectural diagrams and technical design documents for all these projects.
• Developed initial version of eCommerce application using the designed architecture as a base version of the other developer teams to follow.
• Created Seam components to bind the data and created action methods for performing the business logic.
• As part of eMergence project, created widgets for showing different types of daily news on cox.com.
• Developed backing beans (Seam components) for widget facelets.
• Wrote iBATIS queries to retrieve data from Oracle database.
• Extensively used Ajax4JSF and RichFaces re-usable components such as Tabs, Menus, Panels, Tree Adapters, Data Tables, Data Scrollers, etc.
• Used JPA ORM annotations to achieve mapping between EJB 3 entities and Oracle relational database.

Java Developer

Confidential

Responsibilities:

• Developed entire mobile device software for OM (Offender Market) devices using Qualcomm BREW API. 100% of the company revenue generated from these tracking devices which runs on the software that I developed.
• Developed customized software for PT (Package Tracking), PMT (Pets Motion Tracking) and VT (Vehicle Tracking) devices using OM device software.
• Implemented store and forward, strap and device tamper recognition features.
• Developed Message Driven Beans for processing various types of device request, status, alert, event and location messages.
• Integrated Spring and Hibernate frameworks with existing Struts, EJB components and Web Services.
• Used Spring implementation of HibernateDAOSupport for data persistence using Hibernate.
• Implemented the client and server side web services for device location, voice, presence query and SMS services using Apache Axis.
• Set up the Omnilink BMF CA (Certification Authority) and certified third party customers to create secure web services.

Research Assistant

Confidential

Responsibilities:

• Designed and implemented a parallel framework for large scale mesh generation.
• Used Message Passing Interface (MPI) for inter-process communication and to perform parallel I/O.
• To achieve performance gain, threads were created and managed with POSIX threads.
• Used METIS library for domain decomposition and advance front technique for mesh generation.
• Achieved load balance and developed several parallel algorithms.
• Successfully tested the framework performance with complicated geometries such as brain, pelvis, mouse skull, and several healthcare items on Cray XD1, SGI Altix 350, and IBM Linux super computers (128, 256 node clusters).
• Published several papers in high performance computing and engineering conferences.