⦁ Experience working in / Understanding of Big data analytics technologies
⦁ Played pivotal roles as an engineer and architect across domains
⦁ Past hands on experience with open source Big data technologies – Spark, HBase, Hadoop, MapR and Map/Reduce, Pig, Hive
⦁ OR exposure to commercial platform Big data technologies from providers such as SAS, IBM or Oracle
⦁ Clear understanding of usage and implementations at scale of NoSQL solutions like Hbase, Cassandra, MongoDB, CouchDB, and be comfortable with commercial solutions too
⦁ Expertise in SQL databases (e.g.
MySQL or Oracle), Analytics platforms (e.g. Pentaho, BO or similar) and OLAP technologies
⦁ Solid technology stack in J2EE and .Net (desirable but not essential)
⦁ Solid understanding of the core R language and scripting requirements
⦁ Must have worked with solutions/projects involving both real time as well as offline analytics involving multiple sources of data
⦁ Must have some understanding of data integration technologies and methodologies (middleware, API driven, ETL tools driven, streaming etc.)
⦁ Be very comfortable with Agile methodologies in order to be able to arrive at difficult engineering decisions quickly
⦁ Must have had experience creating solutions or solution concepts and defending these with technology councils / architect groups
⦁ Worked in projects to integrate enterprise data with high volume and velocity 2nd or 3rd party data from other sources such as Social channels or 3rd party sources such DMPs or aggregators
⦁ Should have seen at least one implementation complete lifecycle implementation and subsequent infrastructure tuning for a major Big Data project
Strong Experience on Big Data, Hadoop,Pig,Hive, Hbase,Spark
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