SUMMARY

• Having 8+ years of IT experience in Design, Development, Maintenance and Support of Big Data Applications and JAVA/J2EE.
• Over 5+ years of experience with Big data Hadoop core and Eco - system components like HDFS, MR, Yarn, Hive, Impala, Sqoop,Python Flume, Oozie, Hbase, Zookeeper and Pig.
• Exposure to Spark, Spark Streaming, Spark MLlib, Scala and Creating the Data Frames handled in Spark with Scala.
• Hands on experience in working on Spark SQL queries, Data frames, and import data from Data sources, perform transformations, perform read/write operations, save the results to output directory into HDFS.
• Experience in using D-Streams, Accumulator, Broadcast variables, RDD caching for Spark Streaming.
• Hands on experience in developing SPARK applications using Spark tools like RDD transformations, Spark core, Spark MLlib, Spark Streaming and Spark SQL.
• Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark.
• Strong experience and knowledge of real time data analytics using Spark, Kafka and Flume.
• Hands on experience in Capturing data from existing relational databases (Oracle, MySQL, SQL and Teradata) that provide SQL interfaces using Sqoop.
• Hands on experience in Sequence files, RC files, Avro, Parquet, RC File and JSON Combiners, Counters, Dynamic Partitions, Bucketing for best practice and performance improvement.
• Skilled in developing Java Map Reduce programs using java API and using hive, pig to perform data analysis, data cleaning and data transformation.
• Experience in Analyzing the SQL scripts and designed the solution to implement using Pyspark.
• Worked with join patterns and implemented Map side joins and Reduce side joins using Map Reduce.
• Developed multiple MapReduce jobs to perform data cleaning and preprocessing.
• Designed HIVE queries & Pig scripts to perform data analysis, data transfer and table design to load data into Hadoop environment.
• Expertise in writing Hive UDF, Generic UDF's to in corporate complex business logic into Hive Queries.
• Extensive experience on importing and exporting data using stream processing platforms like Flume and Kafka.
• Good working experience on AWS infrastructure services Amazon Simple Storage Service (Amazon S3), EMR, lambda functions and Amazon Elastic Compute Cloud (Amazon EC2).
• Expertise in working with Hive data warehouse tool-creating tables, data distribution by implementing partitioning, bucketing, writing and optimizing the HiveQL queries.
• Worked and learned a great deal from AmazonWebServices (AWS) Cloud services like EC2, S3, EBS, RDS and VPC.
• Implemented AWS provides a variety of computing and networking services to meet the needs of applications
• Experience in composing shell scripts to dump the shared information from MySQL servers to HDFS.
• Experience in data workflow scheduler Zoo-Keeper and Oozie to manage Hadoop jobs by Direct Acyclic Graph (DAG) of actions with the control flows.
• Experienced in performance tuning and real time analytics in both relational database and NoSQL database (HBase).
• Worked on Implementing and optimizing Hadoop/MapReduce algorithms for Big Data analytics.
• Experience on Mongo DB, Cassandra and various No-Sql databases like HBase, Neon, Radis etc.
• Experience in setting up the Hadoop clusters, both in-house and as well as on the cloud.
• Profound experience in working with Cloudera (CDH4 &CDH5 ) and Horton Works Hadoop Distributions and Amazon EMR Hadoop distributors on multi-node cluster.
• Exposure towards simplifying and automating big data integration with graphical tools and wizards that generate native code using Talend.
• Exposure in using build tools like Maven, SBT.
• Worked on different file formats (ORCFILE, TEXTFILE) and different Compression Codecs (GZIP, SNAPPY, LZO).
• Good understanding of all aspects of Testing such as Unit, Regression, Agile, White-box, Black-box.
• Good knowledge of Web/Application Servers like Apache Tomcat, IBM WebSphere and Oracle WebLogic.
• Experience as a java Developer in client/server technologies using J2EE Servlets, JSP, JDBC and SQL.
• Expertise in designing and development enterprise applications for J2EE platform using MVC, JSP, Servlets, JDBC, Web Services, Hibernate and designing Web Applications using HTML5, CSS3, AngularJS, Bootstrap.
• Adept in Agile/Scrum methodology and familiar with SDLC life cycle from requirement analysis to system study, designing, testing, de-bugging, documentation and implementation.
• Techno-functional responsibilities include interfacing with users, identifying functional and technical gaps, es timates, designing custom solutions, development, producing, documentation and production support.
• Excellent interpersonal and communication skills, creative, research-minded, technically competent and result-oriented with problem solving and leadership skills.

TECHNICAL SKILLS

Big Data Ecosystem: HDFS, MapReduce, Hadoop, Map Reduce, HDFS, Zookeeper, Hive, YarnPig, Sqoop, Oozie, Flume, Kafka, and Spark.

Operating System: Windows, Linux, Unix.

Database Languages: SQL, PL/SQL, Oracle.

Programming languages: Scala, Java.

Databases: IBM DB2, Oracle, SQL Server, MySQL, RDBMS, Hbase, Cassandra.

Frameworks: Spring, Hibernate, JMS.

IDE: Eclipse, IntelliJ, Pycharm.

Tools: TOAD, SQL Developer, ANT, Log4J.

Web Services: WSDL, SOAP, REST.

ETL Tools: Talend ETL, Talend Studio.

Web/App Server: UNIX server, Apache Tomcat, WebSphere, WebLogic.

Methodologies: Agile, Waterfall, UML, Design Patterns.

PROFESSIONAL EXPERIENCE

Confidential

Sr. Hadoop/spark Developer

Responsibilities:

• Developed PySpark Applications by using python and Implemented Apache Spark data processing project to handle data from SOR sources.
• Analyze the user needs, interact with various SOR's to understand their incoming data structure and ran POC's with best possible processing framework in big data platform.
• Documented the results with various tools and technologies which can be implemented accordingly based on the business use case.
• Developed PySpark and SparkSQL code to process the data in Apache Spark on Amazon EMR to perform the necessary transformations based on the STMs developed
• Worked with the Spark for improving performance and optimization of the existing algorithms in Hadoop using Spark Context, Spark-SQL, Data Frame, Pair RDD's, Spark YARN.
• Developed UNIX shell scripts to load large number of files into HDFS from Linux File System.
• Played a key role in Finalizing the tech stack for our project (GPC) and ran end to end vigorous testing qualifying the user needs as well as tech requirements.
• Ran data formatting scripts in python and created terabyte csv files to be consumed by Hadoop MapReduce jobs.
• Performed Kafka analysis, feature selection, feature extraction using Apache Spark Machine Learning streaming libraries in Python.
• Developed Python code using version control tools like GIT hub and SVN on vagrant machines.
• Collaborated with intra applications teams to fit our business models on existing on-Prem platform setup.
• Experience in creating tables, dropping and altered at run time without blocking updates and queries using HBase and Hive.
• Encoded and decoded json objects using PySpark to create and modify the dataframes in Apache Spark
• Involved in converting Hive/SQL queries into Spark transformations using Spark RDD's.
• Migrated an existing on-premises application to AWS.
• Used AWS services like EC2 and S3 for small data sets.
• Created flow diagrams, UML diagrams of designed architecture to make understand and get approval from product owners and the business teams for all the user requirements requested.
• Writing Scala Applications which runs on Amazon EMR cluster that fetches data from the Amazon S3 location and queue it in the Amazon SQS (simple Queue Services) queue.
• Created a AWS Lambda function and configured it to receive events from your S3 bucket.
• Developed the ETL Data pipeline for data loading from centralized Data Lake/ AWS service S3 as a data source to Postgres (RDBMS) using Spark.
• Used Cloud watch to monitor logs and log metrics generated by applications.
• Integrated with Restful API’s to create Service now Incidents when there is a process failure within the batch job.
• Analyzed the SQL scripts and designed the solution to implement using Pyspark.
• Developed a capability to implement audit logging at required stages while applying business logic.
• Implemented spark data frames on huge incoming datasets of various data formats like JSON, CSV, Parquet.
• Actively worked in resolving many of the Tech challenges. One of them is like handling the nested JSON with multiple data sections in the same file and converting them in to spark friendly data frames.
• Re-formatted the end results to SOR's requested formats.

Environment: Spark,AWS, Python, MySQL, Soap, NIFI, Cassandra Spark SQL, Pyspark, Cloudera, HDFS, Hive, Apache Kafka, Sqoop, Scala, Shell scripting, Linux, MySQL Oracle Enterprise DB, Jenkins, Eclipse, Oracle, Git

Confidential - Cambridge, MA

Hadoop&Big Data Developer

Responsibilities:

• Developed Spark Applications by using Java, python and Implemented Apache Spark data processing project to handle data from various RDBMS and Streaming sources.
• 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.
• Consumed XML messages using Kafka & processed xml using Spark Streaming to capture UI updates .
• Developed Preprocessing job using Spark Data frames to flatten Jason documents to flat file.
• Load D-Stream data into Spark RDD and do in memory data Computation to generate Output response.
• Experienced in writing live Real-time Processing and core jobs using Spark Streaming with Kafka as a data pipe-line system.
• Optimize the Pyspark jobs to run on Kubernetes Cluster for faster data processing
• Implemented Elastic Search on Hive data warehouse platform.
• Involved in converting Hive/SQL queries into Spark transformations using Spark RDDs, Python and Scala.
• Wrote Python modules to view and connect the Apache Cassandra instance
• Good understanding of Cassandra architecture, replication strategy, gossip, snitch etc.
• Designed Column families in Cassandra and Ingested data from RDBMS, performed data transformations, and then export the transformed data to Cassandra as per the business requirement.
• Used the Spark DataStax Cassandra Connector to load data to and from Cassandra.
• Experienced in creating data-models for client data sets, 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 requirements.
• 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 analysis.
• Experience in using Avro, Parquet, Crile and JSON file formats, developed UDFs in Hive.
• Develop Autosys job for scheduling.
• Experience working with Apache SOLR for indexing and querying.
• Created custom SOLR Query segments to optimize ideal search matching.
• Worked with Log4j framework for logging debug, info & error data.
• Performed transformations like event joins, filter bot traffic and some pre-aggregations using PIG.
• Developed Sqoop and Kafka Jobs to load data from RDBMS, External Systems into HDFS and HIVE.
• Written several Map reduce Jobs using Java API.
• 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.
• Generated various kinds of reports using Power BI and Tableau based on client’s requirements.
• Used Jira for bug tracking and Bit Bucket to check-in and checkout code changes.
• Worked with Network, database, application and BI teams to ensure data quality and availability.
• Prepare ITSM documents (Implementation Plan, DMIO document, Runbook, PT Metrics) and get signoff from respective teams to implement the code in production.
• Assist in Deployment and provide Technical & Operational support during Install.
• Post implementation support.
• Coordinate with offshore team.
• Review code developed by offshore team and validates the test results.
• Developed spark applications in python(PySpark) on distributed environment to load huge number of CSV files with different schema in to Hive ORC tables.
• Worked on reading and writing multiple data formats like JSON,ORC,Parquet on HDFS using PySpark.
• Responsible for generating actionable insights from complex data to drive real business results for various application teams and worked in Agile Methodology projects extensively.
• Worked with SCRUM team in delivering agreed user stories on time for every Sprint.

Environment: Spark, Spark SQL, Pyspark, Cloudera, HDFS, Hive, Apache Kafka, Sqoop, Java (JDK SE 6, 7), Scala, Shell scripting, Linux, MySQL Oracle Enterprise DB, Python, Jenkins, Eclipse, Oracle, Git, Oozie, MySQL, Soap, NIFI, Cassandra and Agile Methodologies.

Confidential

Hadoop/spark Developer

Responsibilities:

• Worked on migrating MapReduce programs into Spark transformations using Spark and Scala, initially done using python (PySpark).
• Worked on implementing Spark Framework a Java based Web Frame work.
• Developed Spark jobs using Scala on top of Yarn/MRv2 for interactive and Batch Analysis.
• Experienced in querying data using SparkSQL on top of Spark engine for faster data sets processing.
• Worked on the 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
• 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.
• Extracted files from MongoDB through Stream sets and placed in HDFS and processed.
• Used Amazon Dynamo DB to gather and track the event based metrics.
• 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.
• Implemented Custom Sterilizer, interceptors to Mask, created confidential data and filter unwanted records from the event payload in flume.
• Worked with Apache SOLR to implement indexing and wrote Custom SOLR query segments to optimize the search.
• Written java code to format XML documents, uploaded them to Solr server for indexing.
• Experienced 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.
• Experience in working with different join patterns and implemented both Map side and Reduce Side Joins.
• Used AWS Step Functions to monitor series of ETL tasks which are part of workflows.
• Developing Data load functions, which reads the schema of the input data and load the data into a table
• Worked on the Spark SQL for analyzing and applying the transformations on data frames created from the SQS queue and loads them into DB tables.
• Worked on Amazon S3 for persisting the transformed Spark Data Frames in S3 buckets and using Amazon S3 as a Data-lake to the data pipeline running on spark and Map-Reduce.
• Wrote Flume configuration files for importing streaming log data into HBase with Flume.
• Imported logs from web servers with Flume to ingest the data into HDFS. Using Flume and Spool directory loading the data from local system to HDFS.
• Installed and configured pig, written Pig Latin scripts to convert the data from Text file to Avro format.
• Created Partitioned Hive tables and worked on them using HiveQL.
• Loading Data into HBase using Bulk Load and Non-bulk load.
• Installed, Configured Talend ETL on single and multi-server environments.
• Experience 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.
• Experience 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
• Developed MapReduce programs in Java for parsing the raw data and populating staging Tables.
• Experience in setting up the whole app stack, setup and debug log stash to send Apache logs to AWS Elastic search.
• Used Impala connectivity from the User Interface (UI) and query the results using Impala.
• Written and Implemented Teradata Fast load, Multiload and Bteq scripts, DML and DDL.
• Used Zookeeper to coordinate the servers in clusters and to maintain the data consistency.
• Experienced knowledge over designing Restful services using java based API’s like JERSEY.
• 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.
• Supported in setting up QA environment and updating configurations for implementing scripts with Pig, Hive and Sqoop

Environment: Hadoop, HDFS, Hive, Map Reduce, AWS Ec2, SOLR, Impala, MySQL, Sqoop, Kafka, Spark, SQL Talend, Python, PySpark, Yarn, Pig, Oozie, Linux-Ubuntu, Scala, Ab Initio, Maven, Jenkins, Java (JDK 1.6), Cloudera, JUnit, agile methodologies

Confidential, Topeka, KS

Hadoop Developer

Responsibilities:

• Installed and configured Flume, Hive, Pig, Sqoop and Oozie on the Hadoop cluster.
• Collected and aggregated large amounts of web log data from different sources such as webservers, mobile and network devices using Apache Flume and stored the data into HDFS for analysis.
• Installed and configured Hadoop MapReduce, HDFS, developed multiple Map Reduce jobs in java for data cleaning and processing.
• Also used Spark SQL to handle structured data in Hive.
• Involved in making Hive tables, stacking information, composing hive inquiries, producing segments and basins for enhancement.
• Handled importing of data from various data sources, performed transformations using Hive, MapReduce, loaded data into HDFS and extracted data from Teradata into HDFS using Sqoop.
• Written and Implemented Teradata Fast load, Multiload and Bteq scripts, DML and DDL.
• Involved in migrating tables from RDBMS into Hive tables using SQOOP and later generate particular visualizations using Tableau.
• Analyzed substantial data sets by running Hive queries and Pig scripts.
• Created Partitions, Buckets based on State to further process using Bucket based Hive joins.
• Involved in transforming data from Mainframe tables to HDFS, and HBase tables using Sqoop
• Defined the Accumulo tables and loaded data into tables for near real-time data reports.
• Created the Hive external tables using Accumulo connector.
• Written Hive UDFs to sort Structure fields and return complex data type.
• Used distinctive data formats (Text format and ORC format) while stacking the data into HDFS.
• Worked in AWS environment for development and deployment of custom Hadoop applications.
• Strong experience in working with ELASTIC MAP REDUCE (EMR) and setting up environments on Amazon AWS EC2 instances.
• Ability to spin up different AWS instances including EC2-classic and EC2-VPC using cloud formation templates.
• Collected data using Spark Streaming from AWS S3 bucket in near-real-time and performs necessary Transformations and Aggregations to build the data model and persists the data in HDFS
• Imported the data from different sources like AWS S3, LFS into Spark RDD.
• Involved in creating Shell scripts to simplify the execution of all other scripts (Pig, Hive, Sqoop, Impala and MapReduce) and move the data inside and outside of HDFS.
• Creating files and tuned the SQL queries in Hive utilizing HUE.
• Experienced in working with spark eco system using Spark SQL and Scala queries on different formats like Text file, CSV file.
• Designed Power BI data visualization utilizing cross tabs, maps, scatter plots, pie, bar and density charts.
• Configured and deployed Azure Automation Scripts for a multitude of applications utilizing the Azure stack (Including Compute, Web & Mobile, Blobs, ADF, Resource Groups, Azure Data Lake, HDInsight Clusters, Azure Data Factory, Azure SQL, Cloud Services, and ARM), Services and Utilities focusing on Automation.
• Expertized in implementing Spark using Scala and Spark SQL for faster testing and processing of data responsible to manage data from different sources.
• Worked with NoSQL databases like Hbase in making the tables to load expansive arrangements of semi structured data.
• Designed the ETL process and created the high level design document including the logical data flows, source data extraction process, the database staging, job scheduling and Error Handling
• Developed and designed ETL Jobs using Talend Integration Suite in Talend 5.2.2
• Created ETL Mapping with Talend Integration Suite to pull data from Source, apply transformations, and load data into target database.

Environment: Hadoop, Cloudera, HDFS, MapReduce, YARN, Hive, Pig, Sqoop, Hbase, Apache Spark, Accumulo, Oozie Scheduler, Kerberos, AWS, Tableau, Java, Talend, HUE, HCATALOG, Flume, Solr, Git, Maven.

Confidential

Java/ETL Developer

Responsibilities:

• Prepare Functional Requirement Specification and done coding, bug fixing and support.
• Involved in various phases of Software Development Life Cycle (SDLC) as requirement gathering, data modeling, analysis, architecture design & development for the project.
• Designed the front-end applications, user interactive (UI) web pages using web technologies like HTML, XHTML, and CSS.
• Implemented GUI pages by using JSP, JSTL, HTML, XHTML, CSS, JavaScript, AJAX
• Involved in creation of a queue manager in WebSphere MQ along with the necessary WebSphere MQ objects required for use with WebSphere Data Interchange.
• Developed SOAP based Web Services for Integrating with the Enterprise Information System Tier.
• Use ANT scripts to automate application build and deployment processes.
• Involved in design, development and Modification of PL/SQL stored procedures, functions, packages and triggers to implement business rules into the application.
• Used Struts MVC architecture and SOA to structure the project module logic.
• Developed ETL processes to load data from Flat files, SQL Server and Access into the target Oracle database by applying business logic on transformation mapping for inserting and updating records when loaded.
• Have good Informatica ETL development experience in an offshore and onsite model and involved in ETL Code reviews and testing ETL processes.
• Scheduling the sessions to extract, transform and load data in to warehouse database on Business requirements.
• Struts MVC framework for developing J2EE based web application.
• Extensively used Java multi-threading to implement batch Jobs with JDK 1.5 features.
• Designed an entire messaging interface and Message Topics using WebLogic JMS.
• Implemented the online application using Core Java, JDBC, JSP, Servlets, spring, Hibernate, Web Services, SOAP, and WSDL.
• Migrated data source passwords to encrypted passwords using Vault tool in all the JBoss application servers.
• Used Spring Framework for Dependency injection and integrated with the Hibernate framework.
• Developed Session Beans which encapsulates the workflow logic.
• Used JMS (Java Messaging Service) for asynchronous communication between different modules.
• Developed web components using JSP, Servlets and JDBC.

Environment: Java, J2EE, JDBC, Servlets, HTML, XHTML, CSS, JavaScript, Ajax, JavaScript, MVC, Informatica, ETL, PL/SQL, Struts 1.1, Spring, JSP, JMS, JBoss 4.0, SQL Server 2000,Ant, CVS, PL/SQL, Hibernate, Eclipse, Linux

Confidential 

Java/J2EE Developer

Responsibilities:

• Developed the J2EE application based on the Service Oriented Architecture by employing SOAP and other tools for data exchanges and updates.
• Developed the functionalities using Agile Methodology.
• Used Apache Maven for project management and building the application.
• Used Restful API and SOAP web services for internal and external consumption.
• Used Spring ORM module for integration with Hibernate for persistence layer.
• Involved in writing Hibernate Query Language (HQL) for persistence layer.
• Used Spring MVC, Spring AOP, Spring IOC, Spring Transaction and Oracle to create Club Systems Component.
• Wrote backend jobs based on Core Java & Oracle Data Base to be run daily/weekly.
• Coding the core modules of the application compliant with the Java/J2EE coding standards and Design Patterns.
• Written Java Script, HTML, CSS, Servlets, and JSP for designing GUI of the application.
• Worked on Service-side and Middle-tier technologies, extracting catching strategies/solutions.
• Design data access layer using Data Access Layer J2EE patterns, implementing the MVC architecture Struts Framework for handling databases across multiple locations and display information in presentation layer.
• Used XPath for parsing the XML elements as part of business logic processing.