WHO YOU’LL WORK WITH

You will be a part of the larger Global Technology organization working on Nike’s internal product tools and report to the team’s Engineering Director.  You will work day-to-day with a team of engineers, the team’s Technical Product Manager and Principal Engineers in the organization on software projects to achieve Nike’s business objectives.  You will also engage with other Global Technology functions and teams on organizational and technical goals.

WHO WE ARE LOOKING FOR

We’re looking for a Data Engineer to solve complex software engineering problems supporting Nike’s pursuit of delivering state of the art tools to our Consumer Product and Innovation (CP&I) community. The candidate needs to be highly collaborative with peers, productive in a fast-paced development environment and have depth of native cloud software engineering experience.

WHAT YOU’LL WORK ON

You will be part of and leading a team of engineers building out tooling for our Consumer Product & Innovation team members. We are investing in building modular, configurable and “API-First” capabilities which will be consumed by modern web applications build with the most recent SPA frameworks. You are expected to help coordinate with other teams and provide guidance and coaching for more junior team members.

• Bachelor's degree in Computer Science, Engineering, Data Science, or related field; or equivalent combination of education

• 1-2+ years of hands-on experience in data engineering, software development, or related technical roles

• Foundational proficiency in SQL for data querying and manipulation, with basic working knowledge of Python for data processing, scripting, and automation tasks

• Exposure to Spark or similar distributed data processing frameworks, with understanding of big data concepts and parallel computing principles

• Familiarity with at least one major cloud platform (AWS, Azure, Databricks, or Snowflake) and understanding of cloud-based data storage and processing services

• Basic understanding of data modeling, ETL/ELT processes, and data pipeline fundamentals, with awareness of data streaming technologies and real-time data processing concepts

• Knowledge of version control systems (Git), CI/CD concepts, and DevOps practices related to data engineering workflows and automated deployment pipelines

• Exposure to REST API development and data service integration, with understanding of microservices architecture concepts and basic architectural design patterns

• Awareness of data visualization concepts and dashboard design principles; experience with frameworks such as React, Vue.js, or Angular is a plus

• Strong problem-solving skills, collaborative mindset, and ability to work effectively in highly collaborative environments with demonstrated learning agility and attention to detail