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Big Data Technical Lead (Hadoop/HBase/MapReduce/Pig/Oozie)

Job Title: Big Data Technical Lead (Hadoop/HBase/MapReduce/Pig/Oozie)
Contract Type: Contract
Location: Middlesex, Middlesex
Industry:
Salary: £ Excellent Rate
Start Date: ASAP
Duration: 6 Months
REF: HADOOP/LON/CON/MW
Contact Name: Matt Wandowski
Contact Email: Matt.Wandowski@parallelconsulting.com
Job Published: 12 months ago

Job Description

Big Data Technical Lead (Hadoop/HBase/MapReduce/Pig/Oozie and Flume)

Our client, a leading technology company based in Middlesex (Staines) is in search of a forward thinking Big Data specialist to join an existing team at an exciting stage of a specialist Big Data project.

You will be responsible for:
-Completing a project through Agile methodologies such as Kanban and scrum, taking part in daily progress meetings and relaying back updates to the Technical Delivery Manager
-Creating and designing inspiring solutions which can meet objectives that add value to the business
-Managing your own workload as well as the output of the team of Developers, Quality Analysts through setting clear daily objectives
-Working with other departments of the business and be recognized as the SME of Big Data Development

You should be someone who is continually looking to develop as well as inspire those around you and be recognized as the 'go to' technical person in the team.

The ideal candidate must have:
-A strong technical background as well as experience of leading a development team
-Experience working with the Hadoop eco-system including HBase, MapReduce, Pig, Hive, Oozie
-Deep understanding of Java or other similar programming languages

This is initially a 6-month contract with likelihood to extend.
All applications submitted will be considered and if successful interviews will be arranged within 24 hours.

Parallel Consulting is a multi-awarding winning, global leader in Analytics & Data Science recruitment.
With over 12 years expertise, we assist our clients within Analytics, Customer & Marketing Insight, Web Analytics, Big Data, Data Science, Credit Risk and BI.