Job Description :
Expertize in building Data Hub or Data lake using Hadoop and AWS technologies and taking this to production (PoC level experience not acceptable)
Preferred Hadoop Distribution is MapR but Cloudera or Horton with very strong experience with Impala can be acceptable
Experience with Impala and other SQL engines with Hadoop on Production (PoC level is not acceptable)
Experience of integrating Impala with Active Directory and Enterprise Security
Experience of working with AWS Redshift and deeper knowledge of architecture
Expertize in using Hive, Spark
Exposure to AWS Services like S3, EC2, Redshift, EMR, Lambda, data pipeline
Strong experience with Python, Linux Shell scripting (Basic command level knowledge at PoC level is not acceptable)
Experience with ETL & Data Ingestion tools (Configuration in Enterprise secure env and data load both) like Informatica, Kafka, Sqoop etc.,
Experience of working with production cluster with AWS EMR or MapR on AWS or Cloudera on AWS.
Exposure to Teradata or Any other DWH
Performance tuning
Excellent Communication & presentation skill
Ability to work with offshore team as needed
Handling different file formats in Hadoop Ecosystem
Preferably data management and DWH background and experience
Exposure to analytics and data science tools
Experience of working in Pharma domain using any Hadoop Distribution (R&D, Sales & Marketing, Supply Chain


Responsible for building Supply Chain Data hub end to end using Hadoop & AWS components• Create reference architecture and technology architecture for Supply Chain data hub• Enable and configure diff technology components in the architecture on AWS• Automation in cluster using Python, Ansible, Shell Scripting etc.,• Capacity planning for processing and storage based on the requirement• Advise on the solution and technology components for diff purpose in the architecture• Compare and recommend tools• Tune queries in SQL engines on Hadoop• Design data pipeline for loading data from SAP and NON SAP enterprise sources• Problem solving and root cause analysis for issues during setup, configuration • Presenting recommendations and solutions.
             

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