At Apple, the business problem is to generate revenue through sales and empower decision-making at scale by redefining how data, intelligence, and design come together.
Requirements
- Proven experience building large-scale distributed data systems (Spark, Databricks, Kafka, Airflow, Snowflake, etc.) in a production environment.
- Deep understanding of data modeling, ETL/ELT frameworks, and ML data pipelines.
- Strong fluency in SQL, Python, and cloud data ecosystems (GCP/AWS).
- Familiarity with AI/ML feature engineering, experiment tracking, and data versioning.
- Experience with decision intelligence, causal inference, or applied machine learning.
- Familiarity with Apple’s data privacy and data sharing standards.
- Experience working in hybrid data-product environments, supporting both operational and strategic decision layers.
Responsibilities
- Own and evolve the data backbone for the decision intelligence platform with Expert Data Management system - that ingests and curates sales programs data..ensuring scalability, quality, and usability across global channel datasets.
- Design and lead data models, pipelines, and APIs that power predictive, prescriptive, and experimental decision tools used by Apple’s sales programs decision makers
- Partner closely with tech infra and data teams to define data requirements, unify source systems, and accelerate data readiness for new features.
- Champion automation, observability, and performance - ensuring the platform delivers reliable, real-time insights with minimal latency.
- Enable cross-functional integration of data across merchandising, staffing, and training programs, aligning architecture with Apple’s data privacy and security principles.
- Mentor and grow a high-performing team of data engineers and analysts; foster a culture of technical excellence, creativity, and collaboration.
- Drive innovation in AI-native data architecture - including streaming, feature stores, model-serving infrastructure, and feedback loops.
Other
- 15+ years experience in data engineering or architecture roles, with 5+ years experience managing engineering teams at scale.
- BS/MS in Computer Science, Data Engineering, or related technical discipline.
- Excellent cross-functional communication skills; proven ability to partner with product, engineering, and business leaders to prioritize and deliver with clarity.
- A design-minded approach - valuing simplicity, trust, and user empathy as much as performance.
- Advanced degrees or certifications in data architecture, AI systems, or cloud platforms are a plus.
