*share resume to: [email protected] <[email protected]>*

*Need US Citizen/Green Card/GC(EAD)/H4(EAD)/OPT(EAD)/L2(EAD)/TN Visa*


*Opportunity 4: Nike*

*Top Three Skills:*


*AWS, Python/SQL, PySpark. Scala is a plus. Spark Streaming.*



*Duration: 12 Months+*

*Location: Beaverton, OR*


*Interview Process: TEKsystems will be handling the screening,
interviewing, and candidate selections *

*Start Date: 2 Weeks after offer accepted*



Notes: Nike is embracing Big Data technologies to enable data-driven
decisions. We’re looking to expand our Big Data Engineering team to keep
pace. As a Sr. Big Data Engineer you will work with a variety of talented
Nike teammates and be a driving force for building solutions for Nike
Digital. You will be working on projects related to consumer behavior,
commerce, and consumer touchpoints.

Responsibilities:
• Design and implement distributed data processing pipelines using Spark,
Hive, Python, and other tools and languages prevalent in the Hadoop
ecosystem. Ability to design and implement end to end solution.
• Experience publishing RESTful API’s to enable real-time data consumption
using OpenAPI specifications
• Experience with open source NOSQL technologies such as HBase, DynamoDB,
Cassandra
• Familiar with Distributed Stream Processing frameworks for Fast & Big
Data like ApacheSpark, Flink, Kafka stream
• Build utilities, user defined functions, and frameworks to better enable
data flow patterns.
• Work with architecture/engineering leads and other teams to ensure
quality solutions are implements, and engineering best practices are
defined and adhered to.
• Experience in Business Rule management systems like Drools


Qualification:
• MS/BS degree in a computer science or related discipline
• 6+ years’ experience in large-scale software development
• 3+ year experience in Big Data technologies
• Strong programming skills in Java/Scala, Python, Shell scripting, and SQL
• Strong development skills around Spark, MapReduce, and Hive
• Strong skills around developing RESTful API’s

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