Chanakya M Email & Phone Number

• Administered, maintained, provisioned, patched, and maintained Cloudera Hadoop clusters on Linux.• Responsible for building scalable distributed data solutions using Hadoop. • Developed multiple Map Reduce jobs in java for data cleaning and preprocessing. • Developed Map Reduce pipeline jobs to process the data and create necessary HFiles. • Involved in loading the created HFiles into HBase for faster access of large customer base without taking Performance hit. • Worked in AWS environment for development and deployment of Custom Hadoop Applications. • Involved in creation and designing of data ingest pipelines using technologies such as Apache Strom and Kafka. • Developed Spark scripts by using Scala shell commands as per the requirement. • Implemented discretization and binning, data wrangling: cleaning, transforming, merging, and reshaping data frames using Python. • Created HBase tables to store various data formats of PII data coming from different portfolios. • Collecting and aggregating large amounts of log data using Apache Flume and staging data in HDFS for further analysis • Involved in managing and reviewing Hadoop log files. • Responsible to manage data coming from different sources. • Involved in creating Pig tables, loading with data, and writing Pig Latin queries which will run internally in Map Reduce way. • Experienced in Using Pig as ETL tool to do Transformations, even joins and some pre-aggregations before storing the data onto HDFS. • Transferred the data using Informatica tool from AWS S3 to AWS Redshift. Involved in file movements between HDFS and AWS S3. • Create a complete processing engine, based on Hortonworks' distribution, enhanced to performance. • Provide batch processing solution to certain unstructured and large volume of data by using Hadoop Map Reduce framework. • Developed Spark code to using Scala and Spark-SQL for faster processing and testing. • Used AvroSerdes to handle Avro Format Data in Hive and Impala.

Dallas, Texas, United States

• Administered, maintained, provisioned, patched, and maintained Cloudera Hadoop clusters on Linux.• Developed Spark code using Java, Scala for faster testing and data processing. • Experience with batch processing of data sources using Apache Spark. • Experience with real time processing of data sources using Apache Spark Streaming. • 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 Kafka in near real time and Persists into HBase. • Worked on a product team using Agile Scrum methodology to design, develop, deploy, and support solutions that leverage the Client big data platform. • Experienced in handling large datasets using Partitions, Spark in Memory capabilities, Broadcasts in Spark, Effective & efficient Joins, Transformations and other during ingestion process itself. • Optimized MapReduce Jobs to use HDFS efficiently by using various compression mechanisms. • Involved in creation and designing of data ingest pipelines using technologies such as Apache Spark and Kafka • Worked on migrating Map Reduce programs into Spark transformations using Spark and Scala. • Created External Hive Table on top of parsed data. • Experienced in performance tuning of Spark Applications for setting right Batch Interval time, correct level of Parallelism and memory tuning.• Automating and scheduling the Sqoop, Map Reduce and Spark jobs in a timely manner using Unix Shell Scripts and Control-M. • Created Unit Test Documents and performing unit testing. • Used Jira for bug tracking and Quick Build for continuous Integration. • Worked on Data serialization formats for converting complex objects into sequence bits by using Avro, Parquet, Json, CSV formats. • Loading data into HBase using Bulk Load and Non-bulk load. • Involved in transforming data from Mainframe tables to HDFS, and HBASE tables using Sqoop. • Hive QL scripts to create, load, query tables in Hive.

Charlotte, North Carolina, United States

• Extensively worked on Hadoop eco-systems including Hive, Spark Streaming with MapR distribution. • Implemented J2EE Design Patterns like DAO, Singleton, and Factory. • Managed connectivity using JDBC for querying/inserting & data management including triggers and stored procedures. • Worked on analyzing Hadoop cluster and different big data analytic tools including Pig, HBase database and Sqoop. • Upgraded the Hadoop Cluster from CDH3 to CDH4, setting up High Availability Cluster and integrating Hive with existing applications. • Worked on NoSQL support enterprise production and loading data into HBase using Impala and Sqoop. • Performed multiple MapReduce jobs in Pig and Hive for data cleaning and pre-processing. • Build Hadoop solutions for big data problems using MR1 and MR2 in YARN. • Handled importing of data from various data sources, performed transformations using Hive, PIG, and loaded data into HDFS. • Worked on data using Sqoop from HDFS to Relational Database Systems and vice-versa. Maintaining and troubleshooting. • Developed the Java/J2EE based multi-threaded application, which is built on top of the strut’s framework. • Used Spring/MVC framework to enable the interactions between JSP/View layer and implemented different design patterns with J2EE and XML technology. • Exploring with Spark to improve the performance and optimization of the existing algorithms in Hadoop using Spark context, Spark-SQL, Data Frame, pair RDD's. • Created Hive Tables, loaded claims data from Oracle using Sqoop and loaded the processed data into target database. • Involved in PL/SQL query optimization to reduce the overall run time of stored procedures. • Exported data from HDFS to RDBMS via Sqoop for Business Intelligence, visualization, and user report generation. • Implemented the J2EE design patterns Data Access Object (DAO), Session Façade and Business Delegate.

Durham, North Carolina, United States

• Interacted with business analyst to understand the requirements to ensure correct modules been built to meet business requirements. • Participated in the daily SCRUM meetings to produce quality enhancements within time. • Developed UML using Case diagrams, Class diagrams, and Sequence diagrams using Rational Software Architect • Spring MVC model integration for front-end request action controller. • Developed web screens in JSP, JSTL, CSS and client-side validation using jQuery. • Developed Web services to allow communication between application through SOAP over HTTP using Apache CXF • Configured JMS on Web Sphere Server for asynchronous messaging through implementation of Message Driven Beans (MDB). • Used Spring ORM module for integration with Hibernate for persistence layer. • Implemented the application using the concrete principles laid down by several design patterns such as Session Façade, Business Delegate, Singleton, Data Access Object, and Service Locator. • Developed the application in J2EE Application Server environment with IBM WebSphere as deployment server with RAD as development IDE. • Used JIRA for defect tracking and project management. • Developed and designed XML Schemas to transport and store data. XML was used to simplify data and allow for Platform Changes, as well as making data more available across the applications distributed platforms. • Extensively used XSLT to transform XML documents to HTML. • Wrote custom jQuery plugins and developed JavaScript functions to build a bleeding-edge, AJAX-driven user interface. • Developed unit and functional test cases using J-Unit.• Maven and Jenkins used for the automatic build process. • Used Log4J utility to log error, info, and debug messages. • Used Rational Clear Case for version controlling.