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USM Business Systems

Core Java Developer/ Software Engineer With AWS, Big Data/Hadoop

Reposted 8 Days Ago
In-Office
Boston, MA, USA
Mid level
In-Office
Boston, MA, USA
Mid level
Join an elite engineering team to develop massive data processing systems using Core Java and AWS, focusing on Big Data and performance optimization.
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Company Description

USM Business Systems

Job Description

Role: Core Java Developer/ Software Engineer

Location: Boston, MA

Duration: Open Duration – Long Term

Interview: Phone and F2F

Required Skills & Expr : Core Java, AWS, Big Data/Hadoop

Description:

  • Come join an elite engineering team in downtown Boston that is moving the mark for advanced analytics; building a better customer experience across huge swaths of the internet.
  • Massive data processing system (call it Big Data if that makes you feel better) that hits BILLIONS of transactions per day.

Your Java concurrency expertise is needed to bolster the production environment:

  • Large-scale, distributed system -- thousands of machines, petabytes of data.
  • Bleeding edge Big Data and Machine Learning applications and supporting infrastructure; e.g., Spark, Redshift, and Kinesis.
  • Needs to be built for massive scale and needs the best-of-the-best talent.
  • Java is likely your weapon of choice, but you are a true computer scientist that understands the fundamentals and the language is a detail. You have likely played around with some of the newer functional programming languages (Scala, Haskell, etc).
  • Software engineering is not just a job, it is your passion.
  • You have deep experience in multithreading, real-time programming, and performance optimization techniques.
  • Experience developing large-scale, high-performance distributed systems.
  • You are comfortable with many AWS services.
  • You have worked within the Hadoop / Big Data ecosystem.

Additional Information

All your information will be kept confidential according to EEO guidelines.

Top Skills

AWS
Big Data
Core Java
Hadoop
Kinesis
Redshift
Spark

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