Roles and Responsibilities:
Company is looking for an AWS Big Data Engineer Lead who will work on the internal and customer based projects . Company is looking for someone who cares about the quality of code and who is passionate about providing the best solution to meet the client needs and anticipate their future needs based on an understanding of the market. Someone who worked on Hadoop projects including processing and data representation using either Cloudera, Hortonworks OR MapR.
7-12 years of overall experience.
7 years of technical solutions experience including 3+ years in a combination of relevant Big Data/Analytics areas including Hadoop and other industry Big Data frameworks, underlying infrastructure for Big Data solutions (clustered/distributed computing, storage, Data center networking).
Implemented at least 2 Big Data projects from start till roll out.
Deployment of a large distributed Big Data application
Experience designing, building and operating cloud services in IT, System integrator or service provider
High level of experience with Java / Python / Scala
Ability to demonstrate micro/macro designing and familiar with unix commands and basic work experience in unix shell scripting
Good exposure and experience in cluster administration and Enterprise Big Data landscape preparation from scratch
Technology expertise of solutioning in Hadoop, Hive, Spark / PySpark, SQL, Oozie
Excellent communication skills (verbal and written)
Should possess time management skills and should be able to work under serious deadlines
The candidate should have an ability to work in a team environment as well as work individually, should be a self-starter
Seventh Contact Hiring Solutions (SCHS) is a professionally managed recruitment services providers based in Pune. We provide our services to companies in the IT and Engineering sectors in Pune, Other cities in India, Middle East, UK, South Africa.
Functions : IT
Industries : IT/Computers - Hardware, IT/Computers - Software
Skills/Roles I hire for: IT
level Hiring For: Junior Level, Mid Level, High Level
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