Open to remote work except in South Dakota, Vermont and West Virginia.

The annual base salary for this position ranges from $119,400.00 in our lowest geographic market to $267,500.00 in our highest geographic market. Actual salary will vary based on a candidate's location, qualifications, skills and experience.

Information about benefits can be found here.
 

At Nike’s Global Places & Services (GPS) organization, we design and bring to life physical environments and experiences for Nike and the athlete* in more than 100 cities around the world. We work every day to make location a competitive advantage by delivering against our key capabilities: location, physical environments, events, sport, nutrition and mobility.

WHO WE ARE LOOKING FOR

We’re looking for an Analytics Infrastructure Lead to join the GPS Intelligence (GPSI) team in creating and developing Location-based Analytics. This role will manage data engineering and the analytics infrastructure strategy for GPSi, and will also be responsible for communicating the Data Product roadmap to cross-functional stakeholders.

The candidate needs to have strong technical skills with a background in data engineering as well as development experience with front-end applications. Candidates should have a background working with statistics, data modeling, and have a strong competency in AI/ML. Candidates should also have the ability to synthesize complex information into concise and meaningful insights, demonstrating the ability to translate business requirements for analytics/reporting solutions back to their technical team members.

WHAT YOU WILL WORK ON

If this is you, you’ll be working with Global Places and Services teams on a daily basis and often interacting/collaborating with business partner functions who require Location data and reporting. You will be leading the design, development, and maintenance of the analytics infrastructure that supports data science, analytics and reporting needs for the GPS group. This role will be responsible for overseeing the translation of business needs into functional code for analysis and reporting solutions.  In addition, the Analytics Infrastructure Lead will connect with our Nike Tech partners regarding models, architecture and best practices for data solutions. 

WHO YOU WILL WORK WITH

This role reports to the Director of GPS Intelligence and is a member of the GPS Intelligence team within Global Operations. In this role you will work closely with other GPS Intelligence team members as well as teams throughout GPS on a global scale. Your primary stakeholders will sit in the core functions of GPS (Global Places and Global Services). You will also collaborate with Nike business partners in Technology, Security, HR and  Legal to support the creation and maintenance of GPS analytics and data solutions.

WHAT YOU BRING

Required:

• Bachelor’s degree in a quantitative field with 8+ years of relevant industry experience; analytics or computer science background preferred.

• Strong understanding of common coding languages (Python, SQL, R) with demonstrated ability to learn and apply new skills.

• Familiarity with common data science/analytics software tools (e.g. Jupyter Notebook, SQL consoles, Hadoop, Spark) and cloud computing platforms (e.g. Amazon Web Services).

• Proficiency in Snowflake, including data modeling, performance optimization, and advanced querying.

• Experience with source control systems (e.g., Git) for efficient version management and collaboration.

• Expertise in Tableau and Tableau Prep for advanced data visualization and preparation.

• Solid understanding of statistical modeling for data-driven insights and predictive analysis.

• Familiarity with AI/ML concepts and frameworks to support machine learning model deployment and integration.

• Ability to communicate complex technical concepts in clear, business-friendly language.

Preferred:

• Strong background in data architecture, relational database design, and data modeling.

• Familiarity with security and role-based access control.

• Experience with CI/CD tools, preferably Jenkins, and UNIX scripting (Bash) for automation.

• Knowledge of data quality testing, test-driven development, and master data management.