Lead DevOps Engineer - Demand Sensing, Enterprise Data & Analytics

NIKE   •  

Beaverton, OR

Industry: Retail & Consumer Goods


Not Specified years

Posted 26 days ago


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 an exceptional DevOps Software Engineer to join our growing team. You be building automation to enable machine learning engineers to continuously deliver predictive analytics for athlete performance, forecasting, personalization, and inventory optimization. You will work with a team of architects, platform engineers, and machine learning engineers to come up with new and interesting models, test them, and productionalize and scale them in the cloud as APIs, stream processing, or massive batch processing. We are looking for a high energy individual with experience developing cloud native applications, APIs, and data pipelines that values automation, testing, and security. You will orchestrate cloud, containers, 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. Above all, your work will accelerate Nike's core mission of serving Athletes*.

What you’ll do

  • Build cloud infrastructure following the DevOps model
  • Design and implement public and internal APIs
  • Design real-time and batch data pipelines machine learning, collaborative filtering, NLP, and deep learning methods to massive data sets
  • Support investigation of new cloud services, software packages/tools, APIs, container management, and distributed systems, to continuously deliver quality analytics and machine learning at scale.
  • Collaborate with a cross functional agile team of software engineers, data engineers, ML experts, and others to build new product features
  • Enable rapid iteration and product quality through continuous A/B testing


  • Bachelor's Degree in computer science, software engineering, or related field. Masters or Ph.D. preferred.
  • Rock solid software engineer with demonstrated experience in enabling DevOps for Machine Learning, AI or distributed systems development.
  • Experience with any system configuration management tool, such as Ansible, Puppet, or Chef
  • Experience with CI/CD infrastructure using Git, Jenkins, or similar tools
  • Experience with Docker, Kubernetes, Mesos, containers, and related tools and systems
  • Experience with AWS components and services, particularly, CloudFormation, IAM, ECS/EKS, EMR, S3, and Lambda/Serverless
  • Strong Python, Go, shell scripting, and SQL
  • Experience writing automation to deploy R (RStudio), Spark ML, and/or Python apps (pandas, numpy, scipy, etc.)
  • You care about agile software processes, data-driven development, reliability, and responsible experimentation.
  • You preferably have experience with data processing and storage frameworks like Airflow, Hadoop or S3, Snowflake, Spark, Flink, Cassandra or Dynamo, Kafka, etc.
  • You preferably have community contributions, project code, or work on open source to share with us

Job ID: 00408359