- Around 8+ years of professional experience in IT with 5+ years of experience in Bigdata technologies including Hadoop and Spark
- Extensively worked on Spark, Hive, PIG, MapReduce, Sqoop, Kafka, Oozie, HBase, Yarn and Hue.
- Hands on experience in programming using Java, Python, Scala and SQL.
- Sound knowledge of architecture of Distributed Systems and parallel processing frameworks.
- Designed and implemented end - to-end data pipelines to processes and analyze massive amounts of data.
- Experienced in working with various Hadoop distributions mainly Cloudera (CDH), Hortonworks (HDP) and Amazon EMR.
- Experienced in developing production ready spark application using Spark RDD Apis, Data frames, Spark-SQL and Spark-Streaming API's.
- Worked extensively on fine tuning spark applications to improve performance and trouble shooting failures in spark applications.
- Strong experience in using D-Streams for spark streaming, accumulators, Broadcast variables, different levels of caching and optimization techniques for spark jobs
- Proficient in importing/exporting data from RDBMS to HDFS using Sqoop.
- Strong knowledge and hands on experience in developing MapReduce jobs.
- Developed Ad-hoc queries to load and transform data in Hive.
- Well versed with writing Hive DDL's, developing customized UDF’s in Hive.
- Designed and implemented Hive and Pig UDFs using Java for evaluation, filtering, loading and storing of data.
- Solid experience in working with csv, text, sequential, avro, parquet, orc, json formats of data.
- Experience in transferring Streaming data from different data sources into HDFS and HBase using Apache Kafka and Flume
- Experienced in using Oozie schedulers and Unix Scripting to implement Cron jobs that execute different kind of Hadoop actions
- Strong knowledge of NoSQL databases and worked with HBase, Cassandra and Mongo DB.
- Extensively used various IDE’s like IntelliJ, NetBeans and Eclipse
- Experienced in working with cloud services such as EMR, S3, EC2, Redshift,Athena.
- Expert in SQL, extensively worked RDBMSs like Oracle, SQL Server, DB2, MySQL and Teradata
- Worked with Apache Nifi to ingest the data into HDFS from variety of sources
- Good understanding of Hadoop Gen1/Gen2 architecture, YARN architecture and its daemons Node manager, Resource manager and App Master and Map Reduce Programming Paradigm
- Proficient and Worked with GIT, Jenkins and Maven.
- Extensive experience in developing and deploying applications using Web Logic, Apache Tomcat and JBOSS.
- Good understanding and Experience with Agile and Waterfall methodologies of Software Development Life Cycle (SDLC).
- Highly motivated, self-learner with a positive attitude, willingness to learn new concepts and accepts challenges.
Big Data Ecosystems: HDFS, MapReduce, YARN, Hive, Storm, Sqoop, Pig, Spark HBase, Scala, Flume, Zookeeper, OozieNO SQL
Databases: HBase, Cassandra, MongoDB
AWS technologies: Data Pipeline, Redshift, EMR
Languages: Java, Scala, Python, SQL, Pig Latin, HiveQL, Shell Scripting.
Database: Microsoft SQL Server, MySQL, Oracle, DB2
Web/Application Servers: Web logic, Web Sphere, JBoss, Tomcat
IDE s & Utilities: Eclipse, IntelliJ, NetBeans
Operating Systems: UNIX, Windows, Mac, LINUX
Business Intelligent tools: Tableau, Splunk, Qlik View
Agile, V: Model, Waterfall Model, Scrum
- Ingested gigabytes of click stream data from external servers such as FTP server and S3 buckets on daily basis using customized home grown Input Adapters.
- Created Sqoop scripts to import/export data from RDBMS to S3 data store.
- Developed various spark applications using Scala to perform various enrichment of these click stream data merged with user profile data.
- Involved in data cleansing, event enrichment, data aggregation, de-normalization and data preparation needed for machine learning and reporting.
- Automated the data flow between the systems and managed flow of information using Apache Nifi.
- Utilized Spark Scala API to implement batch processing of jobs
- Trouble Shooting Spark applications for improved error tolerance.
- Fine-tuning spark applications/jobs to improve the efficiency and overall processing time for the pipelines
- Created Kafka producer API to send live-stream data into various Kafka topics.
- Developed Spark-Streaming applications to consume the data from Kafka topics and to insert the processed streams to HBase.
- Utilized Spark in Memory capabilities, to handle large datasets.
- Used B roadcast variables in Spark, effective & efficient Joins, transformations and other capabilities for data processing.
- Utilized Spark-SQL to event enrichment and also used Spark-sql to prepare various levels of user behavior summaries
- Experienced in working with EMR cluster and S3 in AWS cloud.
- Creating Hive tables, loading and analyzing data using hive scripts. Implemented Partitioning, Dynamic Partitions, Buckets in HIVE.
- Also Used AWS service Redshift to generate the business report as per requirement
- Involved in continuous Integration of application using Jenkins.
- Interacted with the infrastructure, network, database, application and BA teams to ensure data quality and availability
Environment: AWS EMR, Spark, Hive, HDFS, Sqoop, Kafka, Oozie, Hbase, Scala, MapReduce
- Extensively worked on migrating data from traditional RDBMS to HDFS.
- Ingested data into HDFS from Teradata, Mysql using Sqoop.
- Involved in developing spark application to perform ETL kind of operations on the data.
- Modified existing MapReduce jobs to Spark transformations and actions by utilizing Spark RDDs, Dataframes and Spark SQL API’s
- Utilized Hive partitioning, Bucketing and performed various kinds of joins on Hive tables
- Involved in creating Hive external tables to perform ETL on data that is produced on daily basis
- Validated the data being ingested into HIVE for further filtering and cleansing.
- Developed Sqoop jobs for performing incremental loads from RDBMS into HDFS and further applied Spark transformations
- Loaded the data into hive tables from spark and used Parquet columnar format.
- Created Oozie workflows to automate and productionize the data pipelines
- Migrating Map Reduce code into Spark transformations using Spark and Scala.
- Collecting and aggregating large amounts of log data using Apache Flume and staging data in HDFS for further analysis.
- Worked with Tableau to connect to Impala for developing interactive dashboards.
- Designed, documented operational problems by following standards and procedures using JIRA
Environment: Cloudera Hadoop, Spark, Scala, Sqoop, Oozie, Hive, Cent OS, MySQL, Oracle DB, Flume
- Involved in writing Spark applications using Scala to perform various data cleansing, validation, transformation and summarization activities according to the requirement.
- Load the data into Spark RDD and Perform in-memory data computation to generate the output as per the requirements.
- Developed data pipelines using Spark, Hive and Sqoop to ingest, transform and analyze operational data.
- Developed Spark jobs, Hive jobs to summarize and transform data.
- Worked on performance tuning of Spark application to improve performance.
- Performance tuning the Spark jobs by changing the configuration properties and using broadcast variables.
- Real time streaming the data using Spark with Kafka. Responsible for handling Streaming data from web server console logs.
- Worked on different file formats like Text, Sequence files, Avro, Parquet, JSON, XML files and Flat files using Map Reduce Programs.
- Developed daily process to do incremental import of data from DB2 and Teradata into Hive tables using Sqoop.
- Wrote Pig Scripts to generate Map Reduce jobs and performed ETL procedures on the data in HDFS.
- Analyzed the SQL scripts and designed the solution to implement using Scala.
- Solved performance issues in Hive and Pig scripts with understanding of Joins, Group and Aggregation and how does it translate to MR jobs.
- Work with cross functional consulting teams within the data science and analytics team to design, develop and execute solutions to derive business insights and solve clients operational and strategic problems.
- Exported the analyzed data to the relational databases using Sqoop for visualization and to generate reports for the BI team.
- Extensively used Hive/HQL or Hive queries to query data in Hive Tables and loaded data into HBase tables.
- Extensively worked with Partitions, Dynamic Partitioning, Bucketing tables in Hive, designed both Managed and External tables, also worked on optimization of Hive queries.
- Involved in collecting and aggregating large amounts of log data using Flume and staging data in HDFS for further analysis.
- Assisted analytics team by writing Pig and Hive scripts to perform further detailed analysis of the data.
- Designing Oozie workflows for job scheduling and batch processing.
Environment: Java, Scala, Apache Spark, MySQL, CDH, IntelliJ IDEA, Hive, HDFS, YARN, Map Reduce, Sqoop, PIG, Flume, Unix Shell Scripting, Python, Apache Kafka.
Big Data/Hadoop Developer
- Coordinated with business customers to gather business requirements. And, interact with other technical peers to derive Technical requirements and delivered the BRD and TDD documents
- Involved in validating the aggregate table based on the rollup process documented in the data mapping.
- Designed and Modified Database tables and used HBASE Queries to insert and fetch data from tables.
- Involved in loading and transforming large sets of structured, semi structured and unstructured data from relational databases into HDFS using Sqoop imports.
- Responsible for analyzing and cleansing raw data by performing Hive queries and running Pig scripts on data.
- Developed Pig Latin scripts to extract the data from the web server output files to load into HDFS.
- Created Hive tables, loaded data and wrote Hive queries that run within the map.
- Used OOZIE Operational Services for batch processing and scheduling workflows dynamically and created UDF's to store specialized data structures in HBase and Cassandra.
- Hands on experience in application development using RDBMS, and Linux shell scripting.
- Developed and updated social media analytics dashboards on regular basis.
- Create a complete processing engine, based on Hortonworks distribution.
- Manage and review Hadoop log files.
- Developed and generated insights based on brand conversations, which in turn helpful for effectively driving brand awareness, engagement and traffic to social media pages.
- Involved in the identifying, analyzing defects, questionable function error and inconsistencies in output.
Environment: Hadoop, MapReduce, Yarn, Hive, Pig, HBase, Oozie, Sqoop, Oracle 11g, scala, HDFS, Eclipse
- Gathering requirements from end users and create functional requirements.
- Contribute on process flow analyzing the functional requirements
- Development of Graphical user interface for user self-service screen
- Implemented four eyes principle and created quality check process -reusable across all workflow on overall platform level
- Developed Struts Action classes and Validation classes using Struts controller component and Struts validation framework.
- Support in end user training, testing and documentation.
- Implemented Backing beans for handling UI components and stores its state in a scope.
- Worked on implementing EJB Stateless sessions for communicating with Controller.
- Implemented database integration using Hibernate and utilized spring with Hibernate for mapping with Oracle database.
- Worked on Oracle PL/SQL queries to Select, Update and Delete data.
- Worked on MAVEN for build automation. Used GIT for version control
Environment: Java, J2EE, JSP, Maven, Linux, CSS, GIT Oracle, XML, SAX, Rational Rose, UML.
- Involved in developing the application using Java/J2EE platform. Implemented the Model View Control (MVC) structure using Structs.
- Used Spring Core Annotations for Dependency Injection.
- Used Hibernate as persistence framework mapping the ORM objects to table using Hibernate annotations.
- Responsible to write the different service classes and utility API which will be used across the frame work.
- Used Axis to implementing Web Services for integration of different systems.
- Developed Web services component using XML, WSDL and SOAP with DOM parser to transfer and transform data between applications.
- Exposed various capabilities as Web Services using SOAP/WSDL.
- Used SOAP UI for testing the Restful Webservices by sending and SOAP request.
- Used AJAX framework for server communication and seamless user experience.
- Created test framework on Selenium and executed Web testing in Chrome, IE and Mozilla through Web driver.
- Used client-side java scripting: JQUERY for designing TABS and DIALOGBOX.
- Created UNIX shell scripts to automate the build process, to perform regular jobs like file transfers between different hosts.
- Used Log4j for the logging the output to the files.
- Used JUnit/ Eclipse for the unit testing of various modules.
- Involved in production support, monitoring server and error logs and foreseeing the Potential issues and escalating to the higher levels.
Environment: Java, J2EE, JSP, Servlets, Spring, Servlets, Custom Tags, Java Beans, JMS, Hibernate, IBM MQ Series, AJAX, Junit, Log4j, JNDI, Oracle, XML, SAX, Rational Rose, UML.