Nike Senior Manager Analytics Infrastructure 

United States, Oregon, Beaverton 

315158052

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

The annual base salary for this position ranges from $138,400.00 in our lowest geographic market to $327,200.00 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 .

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.

WHAT YOU BRING

Primary

• Python
• SQL
• Snowflak
• Source Control
• Querying
• Tableau and Tableau Prep
• Statistical Models
• AI/ML

Nice-to-haves

• Data architecture and data modeling
• Relational database design (normalization/denormalization, conceptual modeling, physical modeling)
• Security/role-based access control design
• CI/CD experience (ideally Jenkins)
• UNIX scripting (Bash) and automation

Other skills/experience

• Front-end application/data visualization development
• Designing and implementing data quality tests \Test-driven development
• Understanding of master data management
• Explain technical concepts in simplified ‘business’ language
• Bachelor’s degree and minimum of 8 years directly relevant work experience Note: One of the following alternatives may be accepted: PhD or Law + 3 yrs; Masters + 5 yrs or related field or equivalent combination of education and experience
• Formal analytics, data visualization, or computer science background preferred