Senior Data Modeler, MAC BI Activity Intelligence

NIKE, Inc. is transforming its digital activity platforms, including Nike Run Club and Nike Training Club, into AI-powered coaching experiences. MAC BI is building the data and intelligence foundation that enables these experiences.

Who You'll Work With

MAC BI is the business intelligence function for Nike's Marketing, Activity, and Converse organizations. The team owns data pipelines, reporting platforms, and AI-powered insights. This role reports to the Director of Marketing BI and works with engineers, analysts, and data scientists across Beaverton and Bangalore.

What You'll Do

• Design the unified athlete profile data model, harmonizing wearable device streams from Garmin, Apple Watch, COROS, and other vendors.
• Model coaching intelligence data, including training goals, fitness baselines, injury history, coach notes, athlete feedback, and session RPE.
• Design data structures connecting Nike Sport Research Lab sport science models to production coaching recommendations.
• Own Bronze, Silver, and Gold medallion layer design for the Activity domain.
• Produce Source-to-Target Mappings for Activity data sources.
• Resolve schema conflicts and map equivalent metrics across multiple device vendors.
• Define data contracts, API schemas, refresh cadences, service levels, and versioning strategies for downstream consumers.
• Model race, training plan, in-race coaching signal, and post-race performance data.
• Define data quality rules, referential integrity constraints, and business validations.
• Establish and maintain the Activity data dictionary and catalog.
• Own schema evolution strategies for new device vendors, sensor types, sport science models, and coaching features.
• Partner with analysts to ensure model designs support dashboards and analytical use cases.

Must Have

• Bachelor's degree in computer science, data science, data analytics, or a related field, or a suitable combination of education, experience, or training.
• 5+ years of data modeling experience across analytical and operational data systems.
• Experience designing models for large-scale platforms such as Databricks, Snowflake, BigQuery, or equivalent.
• Deep expertise in dimensional modeling, Data Vault, or medallion architectures.
• Experience with multi-source data harmonization.
• Advanced SQL and data profiling skills.
• Experience producing Source-to-Target Mappings.
• Strong collaboration skills with engineering and analytics teams.

Strong Preference

• Experience with IoT, wearable, or sensor data modeling.
• Experience with health, fitness, or sport science data.
• Familiarity with Databricks and Spark physical design considerations.
• Experience with schema evolution and versioning strategies.
• Comfort with asynchronous collaboration across time zones.

Nice to Have

• Familiarity with Nike's internal data platforms, including Sole and Databricks on Nike infrastructure.
• Background in endurance sports, coaching, or sport science.
• Experience with privacy modeling for health and fitness data.
• Experience modeling data for ML and AI consumption.

What Success Looks Like in the First 12 Months

• The unified athlete profile model is in production.
• Source-to-Target Mappings are complete and used by engineers.
• The coaching intelligence model supports the AI Coaching Engine and coaching dashboards.
• The Activity data dictionary is established as the single source of truth.
• Schema evolution processes support new vendors or sensor types without breaking consumers.
• Data quality rules catch issues at ingestion time.

NIKE, Inc. offers a total rewards package, a casual work environment, a diverse and inclusive culture, and opportunities for professional development. Nike is an equal opportunity employer.