Remote Hadoop/Spark engineer jobs

We, at Turing, are looking for talented remote Hadoop/Spark engineers who will be responsible for designing, building, and maintaining the Hadoop application infrastructure and for cleaning, transforming, and analyzing vast amounts of raw data using Apache Spark . Here's the best chance to collaborate with top industry leaders while working with the leading U.S. companies.

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Job description

Job responsibilities

  • Design and code Hadoop applications to analyze data collections
  • Create data processing frameworks
  • Build and optimize Apache Spark ETL pipelines
  • Deliver scalable, cost-effective, and flexible solutions to clients
  • Design and code Hadoop applications to analyze data collections
  • Create data processing frameworks
  • Build and optimize Apache Spark ETL pipelines
  • Deliver scalable, cost-effective, and flexible solutions to clients
  • Participate in iterative, end-to-end application development
  • Ensure timely and high-quality product delivery experience
  • Conduct feasibility analysis, produce functional and design specifications of proposed new features
  • Take initiative in troubleshooting complex issues discovered in customer environments

Minimum requirements

  • Bachelor’s/Master’s degree in Engineering, Computer Science, IT (or equivalent experience)
  • 3+ years of experience as a Hadoop/Spark engineer (rare exceptions for highly skilled developers)
  • Strong experience in Apache Spark development
  • Proficiency in the Hadoop ecosystem, its components, and Big Data infrastructure
  • Bachelor’s/Master’s degree in Engineering, Computer Science, IT (or equivalent experience)
  • 3+ years of experience as a Hadoop/Spark engineer (rare exceptions for highly skilled developers)
  • Strong experience in Apache Spark development
  • Proficiency in the Hadoop ecosystem, its components, and Big Data infrastructure
  • Expert understanding of Hive, HBase, HDFS, and Pig
  • Expertise in established programming languages like Python, Java, Scala, etc.
  • Proficiency in Apache Spark and different Spark Frameworks/Cloud Services
  • Excellent understanding of data loading tools including Sqoop and Flume
  • Ample knowledge of quality processes and estimation techniques
  • Fluent in English to communicate effectively
  • Ability to work full-time (40 hours/week) with a 4 hour overlap with US time zones

Preferred skills

  • Good understanding of SDLC and Agile methodologies
  • Well-versed with UNIX/Linux operating system and development environment
  • Familiarity with performance engineering
  • Great technical, analytical and problem-solving skills
  • Good understanding of SDLC and Agile methodologies
  • Well-versed with UNIX/Linux operating system and development environment
  • Familiarity with performance engineering
  • Great technical, analytical and problem-solving skills
  • Excellent logical thinking and collaborative skills

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