Lead Cloud Engineer / Big Data
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POST DATE 8/25/2016
END DATE 12/19/2016
San Francisco, CA
JOB DESCRIPTIONPosition: Lead Cloud Engineer/Big Data
Location: San Francisco
Seeking a well-rounded Lead Cloud Engineer with a wide breadth and depth of knowledge in software design and development to join the Sling cloud engineering team. Our ideal candidate will have in-depth understanding coupled with experience in leading a team to build horizontally scalable services using J2EE stack, as well as, experience in big data processors (Hadoop) and a strong programming background. Position will work with limited supervision and must be capable of juggling multiple priorities and able to thrive in a fast-paced, demanding environment!
Lead all phases of development cycle with the ownership on end to end delivery and support while standing up in production
Evangelize best practices in architecture, design & clean code
Write server-side code for cloud services layers using J2EE stack, create robust high-volume, scalable applications, & build prototypes quickly
Conduct design reviews and ensure that the design/implementation is highly modular, portable and performance optimized
Lead design, solution architecture and eager to mentor team members
7+ years of overall development experience
2 + years of experience in leading the development of complex, high throughput, multi-tier, highly scalable and fault tolerant customer facing cloud layers using J2EE technology stack
4+ years of experience in building horizontally scalable RESTful services using J2EE technology stack
Hands-on with NoSQL data stores such as Couchbase
Preferred Qualifications: AS MANY AS POSSIBLE FOR CONTRACTORS.
Cozy with messaging - RabbitMQ or Kafka
Breadth and depth of experience in search solutions with Lucene, Solr, SolrCloud, unstructured data mining, search query commands and real time data collections and processing
Heavy experience with the Hadoop ecosystem - HDFS, MapReduce, Pig, Hive, Hbase, Zookeeper etc
Successfully applied scalable algorithms for click stream analysis to model user behavior and engagement.
Competency in statistical modeling and inference
Experience in using predictive techniques on Mahout, such as logistic regression, Naive Bayes, SVM, and decision trees