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Big Data Engineer

McLean, VA
2018-03-16 16:36:04
Job Type: Contract

The Job:
Collaborating as partof a cross-functional Agile team to create and enhance software that enablesstate of the art, next generation Big Data & Fast Data applications
 Building efficient storage for structuredand unstructured data
Developing and deploying distributed computing Big Data applications using OpenSource frameworks like Apache Spark, Apex, Flink, Nifi, Storm and Kafka on AWSCloud
Utilizing programming languages like Java, Scala, Python and Open Source RDBMSand NoSQL databases and Cloud based data warehousing services such as Redshift
Utilizing Hadoop modules such as YARN & MapReduce, and related Apacheprojects such as Hive, Hbase, Pig, and Cassandra
Leveraging DevOps techniques and practices like Continuous Integration,Continuous Deployment, Test Automation, Build Automation and Test DrivenDevelopment to enable the rapid delivery of working code utilizing tools likeJenkins, Maven, Nexus, Chef, Terraform, Ruby, Git and Docker
Performing unit tests and conducting reviews with other team members to makesure your code is rigorously designed, elegantly coded, and effectively tunedfor performance
Basic Qualifications:
 Bachelor’s Degree or military experience
At least 5 years of professional work experience in data warehousing and dataanalytics

At least 4 years of experience in open sourceprogramming languages for data analysis

 At least3 years of Java development for modern data engineering
 At least 3 years of data modelingdevelopment
 At least 1 year of experience workingwith cloud data capabilities
Preferred Qualifications:
 Master's Degree or PhD
5+ years Java development experience
 4+ years of experience in Python, Scala,or R for large scale data analysis
 4+ years' experience with RelationalDatabase Systems and SQL (PostgreSQL or Redshift)
4+ years of UNIX/Linux experience
2+ years of Agile engineering experience
2+ years of experience with the Hadoop Stack
2+ years of experience with Cloud computing (AWS)
1+ years of experience with supervised machine learning



Key Skills: