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Senior Big Data Engineer (Hadoop, Jenkins, Spark, Hive, Map Reduce, Python)
London
A British multinational retailer and much-loved brand seek a Big Data Engineer (Hadoop, Python, Spark, Hive, Map Reduce, Jenkins) who loves to push the boundaries of new technologies and solve real-world business problems. If you are a Big Data Engineer who is naturally curious and inquisitive who perhaps is working on the latest technology but not able to autonomously design end to end software solutions into a productionised operations environment, then this could be for you!
Working as a Big Data Engineer in a senior capacity you will be able to create exceptional personalised customer experiences and solve difficult business problems. This is a very challenging and rewarding opportunity where you will not only mentor other team members and lead design workshops, but you will work on a range of technologies including Impala, Oozie, Mule, Kafka and Python to name a few.
The Big Data development team is growing and as Big Data Engineer (Hadoop, Python, Spark, Hive, Map Reduce, Jenkins) you will be part of a highly collaborative team that is integral to the technical decisions and architectures for the company.
Senior Big Data Engineer – What you will bring;
No one day is the same here, however you will design, build, implement and maintain generic components for ingestion, validation, and structuring of disparate data sources into the Big Data platform. Using industry best practices, you will produce standardised coding designs and document generic solutions to the point they can be re-used by other members of the team to perform builds.
As Big Data Engineer you will interact with the business, architecture or other members of the team to define and refine requirements and test components and peer review.
In return you will receive a competitive salary with industry leading benefits and work for a major retailer pioneering new concepts working with a highly intelligent and gifted team of individuals.
Upload your CV to our database.
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