Junior software engineer Resume PA - Hire IT People

SUMMARY

I am a Senior Hadoop Consultant passionate about big data and Hadoop technologies.
I have experience across several domains like finance and retail to Internet of things.
I have 7 years of IT experience of which 5 years are of Hadoop environment experience.
I have worked with companies like Confidential, Confidential, Confidential and Confidential Consultancy Services managing hadoop clusters ranging from 25 to 300 nodes.
With bachelors from renowned Confidential University Chennai India
I have the latest technical know - how, vast industry experience and aspire to be a renowned data guru and a go to expert to your big data problems.

TECHNICAL SKILLS

Big Data Framework and Eco-Systems: Hadoop, MapReduce, HBase, Spark on Scala, Hive, Pig, HDFS, Zookeeper, Sqoop, Cassandra, MongoDB, Kafka, Oozie, Flume.

J2EE Technologies: Servlets, JSP, JDBC, Junit

Languages: Java, Scala, C/C++, Matlab, Python

Middleware: Hibernate 3.x, Spring MVC, Struts 2.2

Web Technologies: CSS, HTML, XHTML, AJAX, XML, XSLT

Databases: Oracle 8i/9i/10g, MySQL, MS Access

IDE: Eclipse 3.x, 4.x, Eclipse RCP, NetBeans 6, STS 2.0, EditPlus, Notepad++

Design Methodologies: UML, Rational Rose

Version Control Tools: GIT, SVN

Operating Systems: Windows 10/8/7, Linux, UNIX

Tools: Ant, Maven, Putty, Docker

PROFESSIONAL EXPERIENCE

Confidential, Detroit, MI

Sr. Scala Spark Developer

Responsibilities:

Wrote Kafka scripts to import data generated from sensors onto HDFS.
Used Spark Streaming on Scala to construct learner data model from sensor data using MLLib.
Developed workflow in Oozie to orchestrate a series of Pig scripts to remove outliers and redundant data.
Used Hadoop's Map Reduce for analysing the vehicle insurance data to by extracting data sets from data sources such as automobile usage records, driver criminal records, opinions, geographic region detail etc.
Developed workflow in Oozie to orchestrate a series of Pig scripts to remove outliers and redundant data.
Loaded the data into SparkRDD and performed in memory data Computation.
Exported the analysed data to the relational databases using Sqoop for the BI team.

Environment: CDH4.4, MRv1,CDH5.2,MRv2

Tools: Spark 1.4, Pig, Hive, Sqoop, Oozie, Zookeeper

Confidential, Plymouth meeting, PA

Big Data Engineer-Hadoop

Responsibilities:

Built a custom data ingestion layer that takes all posts and writes them to local server-based shared nothing architecture.
Used Apache Kafka for handling real-time user data feeds.
Wrote Apache Storm scripts to perform localized ad targeting, frequency capping on Confidential advertising platform.
Batch processing capabilities were added in later stage of project for scalability and throughput advantages.
Utilized MapR’s distribution of Hadoop to perform Business Analytics using Hive and Oozie to substantially increase throughput.
Used MapR-DB to fine tune ad delivery system.
Performed Hive Join optimization and MapReduce tuning to increase processing speed on cluster

Environment: MapR v3.0-MapR v4.1

Tools: HBase, kafka, Hive, Oozie, Storm

Confidential

Data analyst

Responsibilities:

Wrote flume scripts to import data from CPIC records, self-declaration forms, FFMC license forms into Hadoop cluster.
Wrote custom MapReduce algorithms that performed SWOT analysis of records.
Developed Map-Reduce programs in Java for processing the extracted ventures data.
Developed MapReduce jobs for bulk insertion of Confidential customer and track records from files to CASSANDRA.
Assisted in developing a break-even estimator based on risk metrics using Java, SQL & Groovy.
Increased agility of the system Trades/Market Data Feed. Business logic was rewritten on Groovy DSL. It greatly increase the precision of risk metrics.
Involved in setting up the Hadoop clusters, configuration, monitoring and performance tuning on Amazon Elastic MapReduce and Amazon S3.

Confidential

Junior software engineer

Responsibilities:

Installed and configured the Process Mining tool (PROM Lite) in the development environment.
Worked on the use case of determining the model which depicts the claims processing process and all possible deviations by mining the events. Productiondataof claims was used for the same.
Used SAP HANA for cleaning and modifying the event log. Had experimented with somedata profiling plugins in the PROM tool also.
Thisdatawas fed to the PROM Tool to generate the Petri Net using various algorithms.
Experimented with the Alpha algorithm, fuzzy miner, heuristic miner, ILP miner to generate the model with maximum functional accuracy.
Finally the Inductive Miner Plugin in the PROM tool showed results of generating a Petri Net fitting well into the organizational model in terms of functional representation of all cases.
Social Network analysis of the handover of work among the finance associates processing claims was modelled.

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