Lead Offshore team Resume

SUMMARY

Over 5 years of diverse experience in Information Technology which includes Big Data technologies such as Hadoop and Apache Spark.
Expertise in latest Big Data technology Apache Hadoop, Apache Spark, HDFS, MapReduce, Hive, Spark SQL, Yarn, Mesos.
Hands on experience in AWS cloud services S3, EMR, Athena, EC2, Glue, Cloud formation, Cloud watch, Lambda.
Hands on experience in Python and Java, Data Mining and Big Data Analytics.
Hands on experience in Pyspark Shell script, performance tuning Hive queries.
Programming Experience in different programming languages Java, C, Python, COBOL and databases like Oracle, MySQL, SQL Server.
Highly - motivated, productive and customer-focused team player with strong communication, interpersonal, organizational, time management, analytical and problem solving skills.
Reliable and dedicated with the ability to grasp and apply new procedures quickly; organize and prioritize tasks to meet deadlines.

TECHNICAL SKILLS

Big Data Technology: Apache Spark, Hadoop, Hive, Oozie, Yarn, Map Reduce, HBase, HDFS, Sqoop, Flume, AWS-S3, Machine Learning, Data Mining

Languages: Python, Java, Java Script, SQL, PL/SQL, WSDL, XML,C

CI/CD: Jenkins, Docker, Maven, Github,ArtiFactory

Framework: Map Reduce, MVC, Hibernate

Database: Oracle, SQL Server, MySQL

NoSQL Database: Apache Cassandra, Apache Hbase, MongoDB

Reporting Tools: Qlik Sense, Tableau, Splunk

Operating System: Windows, UNIX, Linux

PROFESSIONAL EXPERIENCE

Confidential

Lead Offshore team

Responsibilities:

To get the optimized solution implementing different AWS services. The data is being moved from on-premises to S3 buckets.
Building data pipelines on the AWS and load data from on-premises to S3 buckets.
Transform and cleanse the data using AWS EMR, Spark and Hive with Python.
Perform SQL queries on AWS with Athena and RedShift.
AWS Glue is used to explore the schema of the data as it arrives.

Confidential

Lead Offshore team

Responsibilities:

Built data pipelines to load and transform large sets of structured, semi structured data.
Involved in writing Spark jobs as per business logic.
Improved performance and optimization of the existing algorithms by exploring different components like Spark Context, Spark-SQL, Data Frame, Pair RDD's, accumulators.
Experienced in defining job flows.
Responsible to manage data coming from different sources.
Supported Map Reduce Programs those were running on the cluster.