Spectrum Consulting

Hadoop Administrator Python Spark MapReduce

  • Job Type: Full Time
  • Industry Type: IT Sector
  • Industry Location: Chennai
  • Experience: 6-10yrs
  • No. of Positions: 14
  • Salary Range: 7-12 lac
  • Primary Skills: Hive Hadoop Jupyter Spark Informatica AWS EMR AWS
  • Secondary Skills: Machine Learning Python MapReduce Scripting
  • Job Location: Chennai
  • Posted Date: 391 days ago
Job Description

 

Job Requirements :

 

- 6+ years of exp in Hadoop Distributions (Preferably AWS EMR). Experience in Hadoop Stack - Hadoop, YARN, MapReduce

- 6+ years of strong experience in Hive, Presto, Spark and Linux OS Experience.

- Expertise in AWS experience - EC2, S3, Cloud watch, IAM, VPC

- Good knowledge of AWS Security and Governance.

- Experience in monitoring and troubleshooting of services.

- Experience in providing on call Support.

- Experience in Scripting using Python and Shell.

- Knowledge on DevOps tools - Terraform, Puppet, Jenkins, Bitbucket.

- Knowledge on Machine learning concepts preferred.

- Knowledge on Jupyter Notebooks.

- Knowledge on Control M scheduling tool

- Knowledge on AWS Bigdata Stack - Sagemaker, Athena, Glue preferred.

- 6 years + exp w Informatica power center, Power exchange.

- Good at communicating issues & follow-up through issue resolution.

- Coordinate and interact with the On-site / Off-shore team to clarify on requirements/issues if any.

- Co-ordination with the Guardian SME's and participate in knowledge transition sessions.

- Work closely with other teams - DBAs, Network, Storage, Scheduling, User Admin, Report Admin, Developers, Data Architects and others to triage issues.

- Responsible for proof-of-concept of new approaches and ideas, technology evaluation, maintain the As Is data architecture, develop To Be and transition architecture.

- Self-motivated and ability to work on his/her individual capacity.

- Ability to identify automation opportunities and implement automation.

Certification: Amazon Certified Solution Architect preferred

 

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