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Big Data Developer

  • San Francisco, CA, USA
  • hot
Job #: 43119
Ranked as #12 on Forbes’ List of 25 Fastest Growing Public Tech Companies for 2017, EPAM is committed to providing our global team of over 24,000 people with inspiring careers from day one. EPAMers lead with passion and honesty, and think creatively. Our people are the source of our success and we value collaboration, try to always understand our customers’ business, and strive for the highest standards of excellence. No matter where you are located, you’ll join a dedicated, diverse community that will help you discover your fullest potential.

DESCRIPTION


You are curious, persistent, logical and clever – a true techie at heart. You enjoy living by the code of your craft and developing elegant solutions for complex problems. If this sounds like you, this could be the perfect opportunity to join EPAM as a Big Data Developer. Scroll down to learn more about the position’s responsibilities and requirements.

We are looking for a Big Data Engineer that will work on collecting, storing, processing, and analyzing of huge sets of data. The primary focus will be on choosing optimal solutions to use for these purposes, then maintaining, implementing, and monitoring them. You will also be responsible for integrating them with the architecture used across the company.
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What You’ll Do

  • Select and integrate any big data tools and frameworks required to provide requested capabilities
  • Implement ETL process
  • Monitor performance and advise on any necessary infrastructure changes
  • Define data retention policies

What You Have

  • Proficient understanding of distributed computing principles
  • Management of Hadoop cluster, with all included services
  • Ability to solve any ongoing issues with operating the cluster
  • Proficiency with Hadoop v2, MapReduce, HDFS
  • Experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming
  • Good knowledge of big data querying tools, such as Pig, Hive, and Impala
  • Experience with Spark
  • Experience with integration of data from multiple data sources
  • Experience with NoSQL databases, such as HBase, Cassandra, MongoDB
  • Knowledge of various ETL techniques and frameworks, such as Flume
  • Experience with various messaging systems, such as Kafka or RabbitMQ
  • Experience with big data ML toolkits, such as Mahout, Spark ML, or H2O (if you are going to integrate machine learning in your big data infrastructure)
  • Good understanding of Lambda Architecture, along with its advantages and drawbacks
  • Experience with Cloudera/MapR/Hortonworks

We offer

  • Medical, Dental and Vision Insurance (Subsidized)
  • Health Savings Account
  • Flexible Spending Accounts (Healthcare, Dependent Care, Commuter)
  • Short-Term and Long-Term Disability (Company Provided)
  • Life and AD&D Insurance (Company Provided)
  • Employee Assistance Program
  • Matched 401(k) Retirement Savings Plan
  • Paid Time Off
  • Legal Plan and Identity Theft Protection
  • Accident Insurance
  • Employee Discounts
  • Pet Insurance

Здравствуйте, чем мы можем вам помочь?


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