Lead Data Engineer - Demand Sensing, Enterprise Data & Analytics

At Nike, we serve athletes. Fueled by the insights of the world's best, we design and create products to elevate human potential on a global scale. And it's on us, the Global Operations Team (GOT), to help bring this mission to life.

We are a diverse lineup of thousands spread across the globe. Together, we are building a smarter, more connected and automated value chain. And we are looking for world-class talent like you to contribute to this journey.

Nike is looking for a seasoned engineer who can lead and grow teams of data engineers and developers to support machine learning engineers and data scientists to deliver scalable machine learning and advanced analytics solutions to customers across our business. You will work on a variety of complex business problems such as forecasting, personalization, and inventory optimization. You will productionalize and scale solutions in the cloud as APIs, stream processing, or massive batch processing. You will leverage big data, parallel processing technologies, advanced analytics, machine learning, and deep learning techniques to quantitatively plan product demand, allocate resources, and target the right customers with the best products. You will foster partnerships with best of breed open source communities, commercial vendors, and universities. Above all, your work will accelerate Nike's core mission of serving Athletes*.

What you'll do

  • Design and build reusable components, frameworks and libraries at scale to support analytics products
  • Design and implement product features in collaboration with business and Technology stakeholders
  • Identify and solve issues concerning data management to improve data quality
  • Clean, prepare and optimize data for ingestion and consumption
  • Collaborate on the implementation of new data management projects and re-structure of the current data architecture
  • Implement automated workflows and routines using workflow scheduling tools
  • Build continuous integration, test-driven development and production deployment frameworks
  • Collaboratively review design, code, test plans and dataset implementation performed by other data engineers in support of maintaining data engineering standards
  • Analyze and profile data for the purpose of designing scalable solutions
  • Troubleshoot data issues and perform root cause analysis to proactively resolve product and operational issues


Qualifications


  • Strong programming experience, Scala and python preferred
  • Experience working with Big Data streaming services such as Kinesis, Kafka, etc.
  • Experience working with NoSQL data stores such as HBase, DynamoDB, etc.
  • Experience handling hundreds of terabytes or petabytes of data
  • Experience building domain-driven Microservices
  • Experience provisioning RESTful API's to enable real-time data consumption
  • Experience in Java
  • Experience working with Hadoop and Big Data processing frameworks (Spark, Hive, Nifi, Spark-Streaming, Flink, etc.)
  • Experience building cloud agonistic solution, good knowledge of AWS, Microsoft Azure and other cloud solution.
  • Demonstrated experience developing distributed systems at scale.
  • Experience with SQL, Data Modeling and SQL Analytical functions
  • Experience participating in key business, architectural and technical decisions
  • Experience designing, estimating and executing for complex software projects


  • Strong programming experience, Scala and python preferred
  • Experience working with Big Data streaming services such as Kinesis, Kafka, etc.
  • Experience working with NoSQL data stores such as HBase, DynamoDB, etc.
  • Experience handling hundreds of terabytes or petabytes of data
  • Experience building domain-driven Microservices
  • Experience provisioning RESTful API's to enable real-time data consumption
  • Experience in Java
  • Experience working with Hadoop and Big Data processing frameworks (Spark, Hive, Nifi, Spark-Streaming, Flink, etc.)
  • Experience building cloud agonistic solution, good knowledge of AWS, Microsoft Azure and other cloud solution.
  • Demonstrated experience developing distributed systems at scale.
  • Experience with SQL, Data Modeling and SQL Analytical functions
  • Experience participating in key business, architectural and technical decisions
  • Experience designing, estimating and executing for complex software projects



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