
Sr Analytics Engineer, Retail Data Products
Cupertino, CAJobSeen 1w agoSeen in employer's feed 1w ago
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Job overview
Apple’s Retail Store Analytics team seeks a Sr Analytics Engineer to create tools that enable data‑driven decisions, partner with cross‑functional teams, build and refine scalable dashboards and AI‑driven data products, and deliver dynamic, intuitive decision support for global retail excellence.
Skills & qualifications
Skills
Qualifications
Full job description
Role Number: 200685523-0836
Summary
Imagine what you could do here! The people here at Apple don’t just create products — they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. At Apple, inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work.
We’re a diverse collective of thinkers and doers, continuously reimagining our products and practices to help people do what they love in new ways. That innovation is inspired by a shared commitment to great work — and to each other. Because learning from the people here means we’re learning from the best. Retail Operations creates the tools and programs that empower our teams to provide, a one of a kind, only at Apple experience. We do this by obsessing over the employee and customer experience, and driving a global strategy that sets the bar.
Retail Store Analytics team is looking for an Analytics Engineer with a dashboarding background, appetite to innovate using AI, and passion to use data at scale to drive global retail excellence. In this role, you will play a critical role in delivering the future direction of Apple Retail Operations by integrating data and AI to delight customers and empower store employees. A successful candidate will possess strong technical business intelligence skills, extensive experience delighting users through easy-to-use dashboards, an understanding of retail store dynamics, and the ability to effectively manage delivery of an extensive reporting roadmap as part of a team.
Description
As an Analytics Engineer on Retail Store Analytics, you will create tools that enable data-driven decisions across Apple Retail Operations. Partnering with Product Management, Data Science, Engineering, and Operations teams, you will build and refine scalable dashboards and data products that delight users — including a centralized hub of canonical dashboards and AI-driven conversational data tools—that deliver dynamic and intuitive decision support.
Minimum Qualifications
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6+ years experience building analytics pipelines in a production development environment for modeling, analysis, and reporting
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6+ years experience coding in SQL or PySpark and Python
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6+ years experience building and maintaining dashboards in Tableau, PowerBI, or Looker with hundreds of users
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Ability to initiate, refine, and complete projects with minimal guidance
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Ability to think critically and and collaborate cross-functionally with other data engineering, data science and analytics stakeholders distilling abstract requirements into clear data products
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Bachelor’s degree in a relevant field (Engineering, Data Science, Business) or equivalent experience
Preferred Qualifications
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Experience building analytics pipelines in production development environment, ideally with Snowflake SQL or PySpark, and pipeline tools like Airflow and dbt
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3+ years experience managing semantic layer in tools like Cube, dbt, Snowflake, or LookML
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3+ years experience developing reusable data visualization assets like Tableau viz extensions
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3+ years experience working with retail data
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Master’s degree in a relevant field (Engineering, Data Science, Business) or equivalent experience
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.
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