Technologies experienced in: JAVA, Scala
Big Data components experienced in: Deep knowledge of Big Data Ecosystem, Spark, Spark Streaming, Kafka, Kafka Stream
Technologies experienced in: JAVA, Scala
Big Data components experienced in: Deep knowledge of Big Data Ecosystem, Spark, Spark Streaming, Kafka, Kafka Streaming, HBase, Hive, Zookeeper, YARN, MapReduce, Kafka, Docker, SQOOP, MongoDB, JDBC, JSON, XML, Google Protocol Buffers etc.
Hadoop distributions experienced in: Cloudera, Hortonworks.
AWS Cloud experience in: ● Fit AWS solutions inside a Big Data ecosystem ● Leverage Apache Hadoop in the context of Amazon EMR ● Identify the components of an Amazon EMR cluster, then launch and configure an Amazon EMR cluster ● Use common programming frameworks available for Amazon EMR. ● Improve the ease of use of Amazon EMR by using Hadoop User Experience (Hue) ● Use in-memory analytics with Apache Spark on Amazon EMR ● Use S3 for storage. ● Identify the benefits of using Amazon Kinesis for near real-time Big Data processing ● Leverage Amazon Redshift to efficiently store and analyze data.
Technical Expertise: Languages – Java SE. Tools – GIT, Maven, Putty, Perforce. Servers –Apache Tomcat Operating System – Windows, UNIX IDE – IntelliJ
Professional Experience:
Clairvoyant Experience – 06/19
Project: ODM (Batch Processing) & Near Real Time (NRT)
Developed a data lake for a client (of financial domain) using Spark with JAVA and Scala, cloud we used is AWS, and for streaming we do spark streaming and kafka as well. To keep data secure and for server authentication, we use Kerberos.
Stacks used: Java 7&8, Data Structure, AWS, Spark, Spark Streaming, Kafka, Kafka Stream, HBase, Hive.
Amdocs Experience: Software Developer - 11/16 - 06/19
Project: Amdocs Data Hub (ADH).
Project was to support and enhance the existing amdocs product (ADH), which takes data from source (Oracle, CSV files etc.) and loads that data to the Hadoop environment. Role was to do enhancement in ADH, analyze the code and fix the bugs. Built some new pipelines from scratch like Kafka Collector, File Collector, CSV collector etc.
Stacks Used: Java 7&8, Data Structure, AWS, Spark, Spark Streaming, Kafka, Kafka Stream, HBase, Hive, Zookeeper, YARN, HQL, SQL.
Intra-Amdocs Inter Unit project: Updation Tool
Description: Development of tool is in Micro Services.
Technologies & Tools: Java, Spring Boot, Rest Services, Couch Base, Core Java, Putty,
Detailed Achievements: Code in spring boot with Rest API’s. Integrate business logic with Couch Base DB.