Data Engineer II - Amazon Devices - Amazon - California City - Wizbii

Data Engineer II - Amazon Devices

  • Par Amazon
  • California City (United States of America)
  • Système d'information / Urbanisation des SI
2018-09-05T00:41:33+0000

Description de l'offre

DESCRIPTION

Consider this challenge: every day, tens of millions of customers with unique interests and needs use Amazon devices as a part of their daily life. They might watch a video on their Fire TV, read a book on their Kindle, play a game on their Fire Tablet, and get a weather forecast from their Echo or any combination of thousands and thousands of other activities. We want to help every customer get more from the devices that they already own by providing them personalized content and recommendations across all of our device touchpoints. How do we do this in a way that puts the individual customer and their unique needs at the center of our communication across our varied devices?
In Devices Engagement we use state-of-the-art machine learning techniques, advanced customer segmentation and a relentless focus on device customer experience to answer this question. This newly created full stack team will create a diverse range of products, ranging from large-scale machine learning systems, to real-time, low-latency recommendation and ranking systems, building algorithms for understanding customer behavior and generating recommendations content, and as well as building customer-facing UIs. A a big data engineer on this team you will work in a collaborative environment with our broader team of team ML scientists, designers, and strategists. You will have a unique opportunity to create and build the programs that will drive direct, measurable impact to our customers, powering features on our devices used by millions and millions of customers every day.

About our team
This team is brand new – created to gets things done to improve the customer experience and increase Amazon device engagement. That means we have no technical debt and the freedom to take advantage of all the new tools and techniques available as we build out our engagement platform. We refuse to accept constraints, internal or external, and have a strong bias for action. We love data and believe that we can use it to deliver epic experiences for our customers. We’re going to build epic stuff. This is your chance to “do it right” with virtually no constraints.

About you
You want to make changes that help millions of customers. You don’t want to simply make something 10% better as a part of an enormous team, but rather you want to invent brand new stuff. You are a data engineer with experience in the areas of 1:1 customer communications, recommendation systems, machine learning, big data and data science. You are interested in being a founding member of a new high performing big data team. You have great problem solving skills. You love keeping abreast of the latest technology and use it to help you innovate. You have strong leadership qualities, great judgment, clear communication skills, and a track record of delivering great products.

Profil recherché

BASIC QUALIFICATIONS

· A Bachelor's degree in Computer Science or a related field is required
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· Experience in designing and building data solutions that are scalable, performant and production ready using recent advances in distributed systems (e.g. MapReduce, MPP architectures, and NoSQL databases)
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· Experience with Redshift, Teradata, Netezza, Greenplum, Vertica or other Massively Parallel Processing (MPP) database platforms
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· Implementation experience with Map Reduce frameworks and Hadoop eco-system tools like Hive (HiveQL) or Pig. Experience with Apache Spark and its libraries
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· Experience processing semi-structured data streams with streaming technologies Kafka, Flume, Spark streaming, Flink, Kinesis or others
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· Experience with in-memory caching and NoSQL database technologies, including Redis, MongoDB, HBase, Dynamodb or Cassandra
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· Experience in applying data structures, algorithms, and object-oriented design, to solve problems
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· Experience creating coherent Logical Data Models that drive physical design

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