|Listed on:||8th January|
|Salary/Rate:||£500 - £700|
|Salary Notes:||per day|
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Hadoop infrastructure Big data Architect - MapReduce - Investment Bank
Hadoop Infrastructure Architect is required whose primary focus will be to manage the MapR (Hadoop) infrastructure of the Investment banks Big Data platform within the production support environment . The hands- on architect will have experience infrastructure architecture experience in delivery of IT projects.
Hands on role - strong data analytics / big data Infrastructure architecture experience in delivery of large systems. Knowledge of Hadoop and ideally MapR - but MapR can be learnt on the job. Many years' experience in IT and with BI and data systems. Technical knowledge of data analytics technologies. Knowledge of Big Data technologies (Hive, Drill, HBase, HDFS Cloudera...) and Hadoop distributions, in particular MapR. Linux OS knowledge. Knowledge of security and authentication topics on Big Data technologies. Management of Hadoop cluster, with all included services. Ability to solve any ongoing issues with operating the cluster. Experience working with ETL technologies. Knowledge of data management tools, e.g. Ab Initio, Callibra. Experience working in onshore/offshore delivery centres, including interaction with geographically distributed clients. Role is a new role to join a small team to review and manage the existing infrastructure the industrialise it so that it is used extensively across the bank in London and internationally.
Highly Desirable: Experience with Spark development optional. Experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming. Experience with NoSQL databases, such as HBase, Cassandra, MongoDB. Experience with various messaging systems, such as Kafka.
The role will involve working closely with the other Data Solution Architects and development teams onshore and offshore to configure and manage the platform.
Key responsibilities include:
Big Data Platform Management
Applicants must be eligible to work in the specified location
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