Hadoop Developer Resume

SUMMARY

Having 1+ years of experience inHadoopframework and related technologies like HDFS, MapReduce, Pig, Hive, Kafka, Cassandra.
Procedural noledge in cleansing and analyzing data using HiveQL, Pig Latin and custom MapReduce programs in Java.
Hands - on experience with Cloudera DistributedHadoop(CDH)
Experience object oriented programming (OOP) concepts usingPython, C++ and PHP.
Experience in importing and exporting data using Sqoop from HDFS to Relational Database Systems and vice-versa
Hands on experience in teh GitHub.
Performed analytics in Hive using various files format like JSON, Avro.
Working noledge of database such as Oracle 8i/9i/10g, Microsoft SQL Server.
Experience in NoSQL databases like Cassandra, MongoDB.
Knowledge on JDBC architecture and common API components forjavaapplications to database connectivity.
Strong Communication and Analytical skills and a demonstrated ability to handle multiple tasks as well as work independently or in a team.
Excellent troubleshooting and debugging skills.
Exceptional abilities in using source code analysis tools automated build process and unit testing.

TECHNICAL SKILLS

Big Data Ecosystem: Hadoop, MapReduce, Pig, Hive, Kafka, Cassandra, CSV.

Hadoop Distributions: Cloudera

Languages: Java, Scala

No SQL Databases: Cassandra, MongoDB

DB Languages: MySQL, PL/SQL

Operating systems: UNIX, LINUX, Mac os and Windows Variants

PROFESSIONAL EXPERIENCE

Hadoop Developer

Confidential

Responsibilities:

Created Partitions, Buckets based on State to further process using Bucket based Hive joins.
Involved in creatingHivetables and loading them with data and writingHivequeries.
Implemented Partioning, Dynamic partitioning in Hive.
Experience in NoSQL Column-Oriented Databases like Cassandra and its Integration with Hadoopcluster.
Designed Cassandra tables to support all teh existing retrieve use cases
Analyzed teh volume of teh existing batch process and designed theKafkaTopic and partition.
Involved in developing Hive DDLs to create, alter and drop Hive tables and storm, &Kafka.
ImplementedKafkaCustom encoders for custom input format to load data intoKafkaPartitions.

Environment: Hadoop, Hive, Map Reduce, Kafka, Cassandra, cloudera.