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DataOps Engineer - Dubai

Careem
Dubai, United Arab Emirates
Posted 5 years ago
18People have clicked1 open position
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Job Details

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Job Description

As a Data Ops Engineer at Careem, you’ll be part of a team that builds solutions and tools to enable, organize and process large amounts of data. You will be working with batch and real-time technologies such as Hadoop, Hive, Spark, Spark streaming, Kafka, Cloud computing, and storage to help Careem becoming a data-driven company.

Some of the problems the team is working on are: building a tool to enable business areas to create real-time metrics, automating jobs and pipelines and delivering fast and reliable software.

Job Requirements

  • 2+ years of hands-on experience in building and managing Scalable Big Data Systems
  • 2+ years of experience working with big data technologies like Spark and/or Kafka
  • Proficiency in at least one of the following scripting languages: python or bash
  • Ability to debug critical issues faced in the Big Data ecosystem and come up with a clear solution and fixes.
  • Understanding of distributed processing tools such as Hadoop, Hive, Zookeeper, Presto, Zeppelin, Airflow etc
  • Ability to dig deeper into the issues of the production critical systems and provide permanent fixes for the system
  • Exposure to open source services of Big Data - Spark, Hive , Presto , Kafka etc
  • Experience implementing CI/CD, and maintaining big data ecosystem
  • Experience with one of the following automation tools: chef, ansible, or puppet
  • 1+ years of experience on Packer / Terraform

Desirable:

  • Experience working with Data Science/Analytical teams and building scalable and stable systems
  • Exposure to enterprise level service such as Cloudera, Databricks, AWS, etc
  • Knowledge of containerization (Docker), and supporting technologies
  • Exposure to AWS data services and technologies (EC2, S3, EMR, Kinesis, Lambda, Glue, Data Pipeline, DynamoDB)
  • Knowledge of Relational Databases and Non Relational Databases, such as Maria, Mysql, Hbase or MongoDB
  • Understanding of the Elastic Search

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