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remote (work from home) jobs for Hadoop in India

EPAM Anywhere is hiring remote Hadoop professionals

remote Hadoop job description

responsibilities
  • You will work in a cross-functional team of Machine Learning engineers and Machine Learning Science to design and code large scale batch and real-time ML pipelines
  • Prototype creative solutions quickly by developing minimum viable products and work with seniors and peers in crafting and implementing the technical vision for the team
  • Communicate and work with geographically distributed cross functional teams
  • Participate in code reviews to assess overall code quality and flexibility
  • Resolve problems and roadblocks as they occur with peers and help unblock junior members of the team. Follow through on details and drive issues to closure
  • Define, develop, and maintain artifacts like technical design or partner documentation
  • Drive for continuous improvement within an agile development team
  • Participate in user story creation in collaboration with the team
  • Support and troubleshoot data and/or system issues as needed
requirements
  • 5+ experience in Java Development
  • You have a degree in software engineering, computer science or a similar field.
  • You are comfortable programming in Python and Scala (or Java)
  • You are knowledgeable in Big Data technologies, in particular Hadoop, Hive, and Spark.
  • You have experience in building real-time applications, preferably in Spark
  • You have a good understanding of machine learning pipelines and machine learning frameworks such as TensorFlow and Pytorch
  • You are familiar with cloud services (e.g., AWS) and workflow orchestration tools (e.g., Airflow)
  • You have experience working with Agile/Scrum methodologies.
nice to have
  • Experience in the e-commerce or travel industry

explore our Hadoop India remote jobs

skill

Java

Machine Learning Engineering, Amazon Web Services, Apache Airflow

clock

40 hrs/week

calendar

12+ months

location
India
Currently, we are looking for a remote Lead Java Developer to join our team.

why apply for our remote Hadoop job in India

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Remote forever

Build your work around your lifestyle with jobs that are remote by design.

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Competitive compensation

Receive a salary on par with global market rates, with pay reviews as you continuously grow.

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Long-term projects

Plan your life and career for years ahead with full-time, long-term projects.

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Social protection

Access all the benefits you deserve — including health insurance, paid leave, stable income, and more depending on your location.

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Guided career growth

Find your mentor among our Skill Advisors and grow your career towards clear and manageable goals.

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Individual project matching

Choose the right project for you with the help of a personal project matching coordinator.

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Free learning

Access the hundreds of free courses, training programs and certification support resources available at Anywhere.

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Anywhere Club

Join our learning and professional networking hub right after successfully passing the Technical Interview.

our webinars

how to apply for the Hadoop in India role

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01
choose a job

Browse open positions at Anywhere and find the one that fits your expertise and career goals. You can also share your CV, and our recruitment team will suggest the most suitable job for you.

02
apply

Send us your application, and the Anywhere recruitment team will promptly review it and get back to you. When signed in, you can monitor your application progress in your profile.

03
interview

With your application successfully reviewed, it’s now time to shine during the interviews. You’ll start with the general one with the recruiter. Next, you’ll showcase your skills at the technical interview, and then discuss final details at the offer interview.

04
get started

After you accept the offer, we will move on with the onboarding process and the paperwork. Then you’ll be matched with a project that fits your professional goals and aspirations best. Apply now to speed up your exciting new start at Anywhere!

apply now

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