- 9+ years of professional experience this includes Analysis, Design, Development, Integration, Deployment and Maintenance of quality software applications using Java/J2EE Technologies and Hadoop technologies.
- Experience in analysis, design, development and integration using Bigdata - Hadoop Technology like MapReduce, Hive, Pig, Sqoop, Ozzie, Kafka, HBase, AWS, Cloudera, Hortonworks, Impala, Avro, Data Processing, Java/J2EE, SQL.
- Experienced in installing, configuring, testing Hadoop ecosystem components on Linux /UNIX including Hadoop Administration (like Hive, pig, Sqoop etc.)
- Expertise in Java, Hadoop Map Reduce, Pig, Hive, Oozie, Sqoop, Flume, Zookeeper,Impala and NoSQL Database.
- Excellent experienced on Hadoop ecosystem, In-depth understanding of Map Reduce and the Hadoop Infrastructure.
- Excellent experience in Amazon, Cloudera and Hortonworks Hadoop distribution and maintaining and optimized AWS infrastructure (EMR EC2, S3, EBS)
- Expertise in developing Spark code using Scala and Spark-SQL/Streaming for faster testing and processing of data.
- Excellent knowledge 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, pig) and NoSQL database MongoDB
- Experienced on usage of NoSQL database column-oriented HBase.
- 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 ofMapReduce/HDFS Framework.
- Experienced in working with MapReduce Design patterns to solve complex MapReduce programs.
- Excellent Knowledge in Talend Big data integration for business demands to work towards Hadoop and NoSQL
- Hands-on programming experience in various technologies like JAVA, J2EE, HTML, XML
- 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.
- Strong experience in analyzing large amounts of data sets writing Pigscripts and Hive queries.
- Extensive experienced in working with structured data using Hive QL, join operations, writing custom UDF's and experienced in optimizing Hive Queries.
- Expertise in Data Development in Hortonworks HDP platform & Hadoop ecosystem tools like Hadoop, HDFS, Spark, Zeppelin, Hive, HBase, SQOOP, flume, Atlas, SOLR, Pig, Falcon, Oozie, Hue, Tez, Apache NiFi, Kafka.
- Experienced in importing and exporting data using Sqoop from HDFS to Relational Database and e xpertise in job workflow scheduling and monitoring tools like Oozie.
- Experienced in Apache Flume for collecting, aggregating and moving huge chunks of data from various sources such as webserver, 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.
- Expert in Amazon EMR, Spark, Kinesis, S3, Boto3, Bean Stalk, ECS, Cloud watch, Lambda, ELB, VPC, Elastic Cache, Dynamo DB, Redshit, RDS, Aethna, Zeppelin & Airflow.
- Experience using various Hadoop Distributions (Cloudera, Hortonworks, MapRetc) to fully implement and leverage new Hadoop features
- Experience working on Bootstrap, Angular JS and Node JS, knockout, ember.js, Java Persistence Architecture (JPA)
- Strong Knowledge on concepts of Data Modeling Star Schema/Snowflake modeling, FACT& Dimensions tables and Logical & Physical data modeling.
- Experienced in working with different scripting technologies like Python, UNIX shell scripts and strong experienced in working with UNIX/LINUX environments, writing shell scripts.
- Excellent knowledge and working experience in Agile & Waterfallmethodologies and expertise in Web pages development using JSP, HTML, Java Script, JQuery and Ajax.
- Expertise in core Java, J2EE, Multithreading, JDBC, Hibernate, Spring, Shell Scripting and proficient in using Java API's for application development.
- Experienced in writing database objects like Stored Procedures, Functions, Triggers, PL/SQL packages and Cursors for Oracle, SQL Server, and MySQL & Sybase databases.
Hadoop/Big Data Technologies: HDFS, Map Reduce, Sqoop, Flume, Pig, Hive, Oozie, impala, Zookeeper and Cloudera Manager, MongoDB, NO SQL Database HBase, Cassandra.
Monitoring and Reporting: Tableau, Custom shell scripts, Hadoop Distribution Horton Works, Cloudera, MapR
Build Tools: Maven, SQL Developer
Programming & Scripting: JAVA, J2EE, HTML, Java script, JQuery, PL/SQL, C, SQL, Shell Scripting, Python.
Databases: Oracle, MY SQL, MS SQL server, Teradata
Version Control: SVN, CVS, GIT
Operating Systems: Linux, Unix, Mac OS-X, Windows 8, Windows 7, Windows Server
Sr. Big Data/Hadoop Architect
Confidential, Minneapolis, MN
- Involved in full life cycle of the project from Design, Analysis, logical and physical architecture modeling, development, Implementation, testing.
- Scripts were written for distribution of query for performance test jobs in Amazon Datalake..
- Created Hive Tables, loaded transactional data from Teradata using Sqoop and Worked with highly unstructured and semi structured data of 2 Petabytes in size
- Developed MapReduce (YARN) jobs for cleaning, accessing and validating the data and c reated and worked Sqoop jobs with incremental load to populate Hive External tables.
- Developed optimal strategies for distributing the web log data over the cluster importing and exporting the stored web log data into HDFS and Hive using Sqoop.
- Apache Hadoop installation & configuration of multiple nodes on AWS EC2 system and d eveloped Pig Latin scripts for replacing the existing legacy process to the Hadoop and the data is fed to AWS S3.
- Responsible for building scalable distributed data solutions using Hadoop Cloudera and d esigned and developed automation test scripts using Python
- Performed data analysis, feature selection, feature extraction using Apache Spark Machine Learning streaming libraries in Python.
- Integrated Apache Storm with Kafka to perform web analytics and to perform click stream data from Kafka to HDFS and w riting Pigscripts to transform raw data from several data sources into forming baseline data.
- Analyzed the SQL scripts and designed the solution to implement using Pyspark and i mplemented HiveGenericUDF's to in corporate business logic into HiveQueries.
- Involved in deploying the applications in AWS and maintains the EC2 (Elastic Computing Cloud) and RDS (Relational Database Services) in amazon web services.
- Responsible for developing data pipeline with Amazon AWS to extract the data from weblogs and store in HDFS and u ploaded streaming data from Kafka to HDFS, HBase and Hive by integrating with storm.
- Analyzed the web log data using the HiveQL to extract number of unique visitors per day, page views, visit duration, most visited page on website.
- Developed REST APIs using Java, Play framework and Akka and u se Scala for coding the components in Play and Akka.
- Supporting data analysis projects by using Elastic MapReduce on the Amazon Web Services (AWS) cloud performed Export and import of data into s3.
- Worked on MongoDB by using CRUD (Create, Read, Update and Delete), Indexing, Replication and Sharding features.
- Involved in designing the row key in Hbase to store Text and JSON as key values in Hbase table and designed row key in such a way to get/scan it in a sorted order.
- 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).
- Creating Hive tables and working on them using Hive QL and d esigned and Implemented Partitioning (Static, Dynamic) Buckets in HIVE.
- Developed multiple POCs using PySpark and deployed on the YARN cluster, compared the performance of Spark, with Hive and SQL and Involved in End-to-End implementation of ETL logic.
- Developed syllabus/Curriculum data pipelines from Syllabus/Curriculum Web Services to HBASE and Hive tables and w orked on Cluster co-ordination services through Zookeeper.
- Worked in Implementation of full lifecycle in Data Modeler, Data warehouses and Datamarts with Star Schemas, Snowflake Schemas, and SCD& Dimensional Modeling Erwin.
- Monitored workload, job performance and capacity planning using Cloudera Manager and i nvolved in build applications using Maven and integrated with CI servers like Jenkins to build jobs.
- Exported the analyzed data to the RDBMS using Sqoop for to generate reports for the BI team and involved in Agile methodologies, daily scrum meetings, spring planning.
- Worked collaboratively with all levels of business stakeholders to architect, implement and test Big Data based analytical solution from disparate sources.
- Troubleshooting, debugging & altering Talend issues, while maintaining the health and performance of the ETL environment.
Sr. Big Data/Hadoop Developer
Confidential, Burlington NJ
- Responsible for installation and configuration of Hive, Pig, Hbase and Sqoop on the Hadoop cluster and created hive tables to store the processed results in a tabular format.
- Configured Spark Streaming to receive real time data from the Apache Kafka and store the stream data to HDFS using Scala.
- Developed the Sqoop scripts in order to make the interaction between Hive and vertica Database.
- Processed data into HDFS by developing solutions and analyzed the data using Map Reduce, PIG, and Hive to produce summary results from Hadoop to downstream systems.
- Build servers using AWS: Importing volumes, launching EC2, creating security groups, auto-scaling, load balancers, Route 53, SES and SNS in the defined virtual private connection.
- Written Map Reduce code to process and parsing the data from various sources and storing parsed data into HBase and Hive using HBase-Hive Integration.
- Streamed AWS log group into Lambda function to create service now incident.
- Involved in loading and transforming large sets of Structured, Semi-Structured and Unstructured data and analyzed them by running Hive queries and Pig scripts.
- Implement enterprise grade platform (mark logic) for ETL from mainframe to NOSQL (C assandra) and c reated Managed tables and External tables in Hive and loaded data from HDFS.
- Developed Spark code by using Scala and Spark-SQL for faster processing and testing and performed complex HiveQL queries on Hive tables.
- Built a streaming application for log analysis using Kafka, spark streaming, Akka and Cassandra.
- Scheduled several time based Oozie workflow by developing Python scripts.
- Developed Pig Latin scripts using operators such as LOAD, STORE, DUMP, FILTER, DISTINCT, FOREACH, GENERATE, GROUP, COGROUP, ORDER, LIMIT, UNION, SPLIT to extract data from data files to load into HDFS.
- Exporting the data using Sqoop to RDBMS servers and processed that data for ETL operations.
- Worked on S3 buckets on AWS to store Cloud Formation Templates and worked on AWS to create EC2 instances.
- Designing ETL Data Pipeline flow to ingest the data from RDBMS source to Hadoop using shell script, sqoop, package and MySQL.
- Optimized the Hive tables using optimization techniques like partitions and bucketing to provide better.
- 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.
- Implementing Hadoop with the AWS EC2 system using a few instances in gathering and analyzing data log files.
- Involved in Spark and Spark Streaming creating RDD's, applying operations -Transformation and Actions.
- Created partitioned tables and loaded data using both static partition and dynamic partition method.
- Developed custom Apache Spark programs in Scala to analyze and transform unstructured data.
- Handled importing of data from various data sources, performed transformations using Hive, MapReduce, loaded data into HDFS and Extracted the data from Oracle into HDFS using Sqoop
- Using Kafka on publish-subscribe messaging as a distributed commit log, have experienced in its fast, scalable and durability.
- Test Driven Development (TDD) process and extensive experience with Agile and SCRUM programming methodology.
- Implemented POC to migrate Map Reduce jobs into Spark RDD transformations using SCALA
- Developed Star and Snow flake schemas based dimensional model to develop the data warehouse and scheduled map reduce jobs in production environment using Oozie scheduler.
- Working on MapR Hadoop platform to implement Big Data solutions using Hive, Map Reduce, shell scripting, and java technologies.
- Involved in Cluster maintenance, Cluster Monitoring and Troubleshooting, Manage and review data backups and log files.
- Worked on setting up and configuring AWS's EMR Clusters and Used Amazon IAM to grant fine-grained access to AWS resources to users
- Worked on Spark, Scala, Python, Storm Impala and designed and implemented map reduce jobs to support distributed processing using java, Hive and Apache Pig
- Analyzing Hadoop cluster and different Big Data analytic tools including Pig, Hive, HBase and Sqoop.
- Improved the Performance by tuning of HIVE and map reduce and research, evaluate and utilize new technologies/tools/frameworks around Hadoop ecosystem
- Created ER diagram for Data Modeling and Developed different kinds of interactive graphs in ER studios.
Hadoop/Big Data Developer
Confidential, Alpharetta, GA
- Responsible for building scalable distributed data solutions using Hadoop
- Designed the projects using MVC architecture providing multiple views using the same model and thereby providing efficient modularity and scalability
- Custom talend jobs to ingest, entich and distribute data in Cloudera Hadoop ecosystem.
- Downloads the data that was generated by sensors from the Patients body activities, the data will be collected in to the HDFS system online aggregators by Kafka.
- 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.
- Improving the performance and optimization of existing algorithms in Hadoop using Spark context, Spark-SQL and Spark YARN using Scala.
- Implemented Spark Core in Scala to process data in memory.
- Performed job functions using Spark API's in Scala for real time analysis and for fast querying purposes.
- Spark Streaming collects this data from Kafka in near-real-time and performs necessary transformations and aggregation on the fly to build the common learner data model and persists the data in NoSQL store (Hbase).
- Have done OOP's and functional programming on SCALA.
- Used Hadoop's Pig, Hive and Map Reduce for analyzing the Health insurance data to help by extracting data sets for meaningful information such as medicines, diseases, symptoms, opinions, geographic region detail etc.
- Enhanced and optimized product Spark code to aggregate, group and run data mining tasks using the Spark framework.
- Handled importing of data from various data sources, performed transformations using MapReduce, Spark and loaded data into HDFS.
- Involved in OLAP model based on Dimension and FACTS for efficient loads of data based on Star Schema structure on levels of reports using multi-dimensional models such as Star Schemas and Snowflake Schema.
- Developed workflow in Oozie to orchestrate a series of Pig scripts to cleanse data, such as removing personal information or merging many small files into a handful of very large, compressed files using pig pipelines in the data preparation stage.
- UsedPig in three distinct workloads like pipelines, iterative processing and research.
- UsedPig UDF's in Python, Java code and uses sampling of large data sets.
- Involved in moving all log files generated from various sources to HDFS for further processing through Flume and process the files by using some piggybank.
- Extensively used PIG to communicate with Hive using HCatalog and HBASE using Handlers.
- Created PIG Latin scripting and Sqoop Scripting.
- Involved in transforming data from legacy tables to HDFS, and HBASE tables using Sqoop
- Implemented exception tracking logic using Pig scripts
- Exported the analyzed data to the relational databases using Sqoop for visualization and to generate reports for the BI team
- Analyzed large amounts of data sets to determine optimal way to aggregate and report on it
Environment: Hadoop, Map Reduce, Spark, shark, Kafka, HDFS, Hive, Pig, Oozie, Core Java, Eclipse, Hbase, Flume, Cloudera, Oracle 10g, UNIX Shell Scripting, Scala, MongoDB, HBase, Cassandra.
Sr. Java/J2EE Developer
Confidential, Columbus, OH
- Used JSF framework to implement MVC design pattern and developed applications using Model-View-Controller architecture using spring MVC
- Design and development of Angular JS UI framework, Spring Rest API services, data business logic and spring boot configuration.
- Wrote JSF managed beans, converters, and validator’s following framework standards and used explicit and implicit navigations for page navigations.
- Designed and developed Persistence layer components using HibernateORM tool.
- UI designed using JSF tags, Apache Tomahawk & Rich faces and Oracle 10g used as backend to store and fetch data.
- Have implemented projects in Rest API Services, Spring boot and AWS deployment.
- Experienced in using IDE's like Eclipse and Net Beans, integration with Maven and creating Real-time Reporting systems and dashboards using xml, MySQL, and Perl
- Involved in developing Rest Controller classes using Spring Boot with Maven and Implemented functionalities File Uploading and Downloading using Spring boot
- Working on Restful web services which enforced a stateless client server and support JSON (few changes from SOAP to RESTFUL Technology) Involved in detailed analysis based on the requirement documents.
- Involved in Design, development and testing of web application and integration projects using Object Oriented technologies such as Core Java, J2EE, Struts, JSP, JDBC, Spring Framework, Hibernate, Java Beans, Web Services (REST/SOAP), XML, XSLT, XSL, and Ant.
- Designing and implementing SOA compliant management and metrics infrastructure for Mule ESB infrastructure utilizing the SOA management components.
- JAX-WS used to interact in front-end module with backend module as they are running in two different servers.
- Responsible for Offshore deliverables and provide design/technical help to the team and review to meet the quality and time lines.
- Provided and implemented numerous solution ideas to improve the performance and stabilize the application.
- Extensively used LDAP Microsoft Active Directory for user authentication while login and Developed unit test cases using JUnit.
- Involved in developing perl script and some other scripts like java script and tomcat is the webserver used to deploy OMS web application.
- Used SOAPLite module to communicate with different web-services based on given WSDL and prepared technical reports &documentation manuals during the program development.
Environment: JDK 1.5, JSF, Spring, Hibernate 3.0, JIRA, Cruise control, Log4j, Tomcat, LDAP, JUNIT, Spring Boot, NetBeans, Windows/UNIX, Angular JS, MVC Framework, Nodejs, HTML, CSS, JASON.
- Performed analysis for the client requirements based on the developed detailed design documents.
- Developed Use Cases, Class Diagrams, Sequence Diagrams and Data Models.
- Developed STRUTS forms and actions for validation of user request data and application functionality.
- Developed programs for accessing the database using JDBC thin driver to execute queries, Prepared statements, Stored Procedures and to manipulate the data in the database
- Designing the database and coding of SQL, PL/SQL, Triggers and Views using IBM DB2.
- Developed Message Driven Beans for asynchronous processing of alerts.
- Used Clearcase for source code control and JUNIT for unit testing.
- Involved in peer code reviews and performed integration testing of the modules. Followed coding and documentation standards.
Environment: Java, Struts, JSP, JDBC, XML, Junit, Rational Rose, CVS, DB2, Windows.