Data Engineer
WHQ
Nike
Inspiration und Support für alle Athlet:innen mit innovativen Produkten, Experiences und Services.Data Engineer – NIKE, Inc., Beaverton, OR. Design and implement data products and features in collaboration with product owners, data analysts, and business partners using Agile and Scrum methodology. Contribute to overall architecture, frameworks and patterns for processing and storing large data volumes. Evaluate and utilize new technologies, tools, and frameworks centered around high-volume data processing. Translate product backlog items into engineering designs and logical units of work. Profile and analyze data for the purpose of designing scalable solutions. Define and apply appropriate data acquisition and consumption strategies for given technical scenarios. Design and implement distributed data processing pipelines using tools and languages prevalent in the big data ecosystem. Build utilities, user defined functions, libraries, and frameworks to better enable data flow patterns. Implement complex automated routines using workflow orchestration tools. Anticipate, identify and tackle issues concerning data management to improve data quality. Build and incorporate automated unit tests and participate in integration testing efforts. Utilize and advance continuous integration and deployment frameworks. Telecommuting is available from anywhere in the U.S., except from AK, AL, AR, DE, HI, IA, ID, IN, KS, KY, LA, MT, ND, NE, NH, NM, NV, OH, OK, RI, SD, VT, WV, and WY.
Must have a Master’s degree in Computer Science, Software Engineering, or Information Technology and 2 years of experience in the job offered or a computer-related occupation. Experience must include:
Spark
Python
AWS S3, EMR, and EC2
Hive
Snowflake
Athena
Cloud computing
Scala
Airflow orchestration
Data engineering
Spark streaming
Apply at www.jobs.nike.com (Job# R-43322)
#LI-DNI
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Airflow Architecture Athena AWS Big Data Computer Science Data management Data quality EC2 Engineering Pipelines Python R Scala Scrum Snowflake Spark Streaming Testing
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