WHO YOU’LL WORK WITH

At Nike, we leverage the power of data and technology to serve athletes around the world. The Data & AI (DAI) team is at the forefront of this mission—building scalable, secure, and intelligent platforms that power decision-making and personalized experiences across the Nike ecosystem.

WHO WE ARE LOOKING FOR:

We are looking for an experienced software engineer with a passion for designing and building robust data platforms and solutions. You thrive in a fast-paced, collaborative environment and have a proven track record of delivering scalable and reliable data platforms and services.

Skillset Required

• 7+ years of experience in software development, with a strong foundation in distributed systems, cloud-native architectures, and data platforms.
• Advanced Knowledge in API services
• Expertise in CI/CD process.
• Expertise in big data technologies such as Apache Spark and real-time streaming technologies like Apache Kafka.
• Strong programming skills in Python, Java or similar language
• Strong Knowledge of SQL.
• Advanced knowledge of a **major cloud platform (AWS, Azure, GCP)**and its ecosystem of data services.
• Proficiency with Infrastructure as Code (IaC) tools like Terraform or AWSCloudFormation, Docker, or Kubernetes
• Strong understanding of advanced data modeling techniques and modern data warehouses and strong Medallion architecture expertise
• Ability to design scalable, fault-tolerant, and maintainable distributed systems.
• Excellent communication and stakeholder management skills.

WHAT YOU’LL WORK ON:

What You’ll Do:

• Design, build, deploy, and own complete, scalable, and reliable end to end, software to data platforms and solutions.
• Lead the technical design of new API services, data pipelines, and systems.
• Build reusable frameworks, libraries, and data management SDKs to improve productivity.
• Build Data Mesh Data products with abstraction.
• Optimize performance and cost-efficiency of Services workload, data workflows and compute layers.
• Collaborate with stakeholders such as data scientists, business analysts, and product managers to understand and translate business requirements into technical solutions.
• Provide t echnical leadership and mentorship to junior engineers.
• Ensure the uptime, reliability, and monitoring of the systems you build and own.