This role pays more than
60%
of similar roles. Most pay
$132,687–$204,512
— the shaded band above.
At the midpoint, this role pays about
$185k
versus about
$169k
for comparable roles.
Based on 240 similar postings.
Employer
About Apple Inc
Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software
Apple Inc currently has
2181 open roles
on FindRole.
Listed pay typically runs
$175,000–$277,600
across 1785 roles with salary data.
The Sr Analytics Engineer, Retail Data Products joins the Retail Store Analytics team to build tools that enable data-driven decisions across global retail operations. This role involves creating and refining scalable dashboards, a centralized hub of canonical dashboards, and AI-driven conversational data tools to support site selection, staffing, scheduling, and operational efficiency. The successful candidate will develop analytics pipelines in production environments and manage semantic layers to provide intuitive decision support for non-technical users. Key technical requirements include extensive experience with SQL, PySpark, Python, and dashboarding tools like Tableau, PowerBI, or Looker. Preferred skills include using Snowflake, Airflow, dbt, Cube, or LookML. The role focuses on the retail domain, specifically solving problems related to store dynamics and improving customer experience programs through integrated data products and advanced conversational business intelligence technologies.
Build and refine scalable dashboards and data products to support retail operations decision-making.
Develop conversational BI tools and AI-driven features to provide intuitive data access for non-technical users.
Create a semantic layer to ensure consistent data modeling across various reporting platforms.
Deliver high-impact dashboards focused on site selection, staffing, scheduling, and operational efficiency.
Build and maintain production analytics pipelines using SQL, PySpark, and tools like dbt or Airflow.
Translate abstract business requirements into clear technical specifications for data products.
Develop reusable data visualization assets to streamline reporting across the retail organization.
What we're looking for
Bachelor's degree in Engineering, Data Science, Business, or equivalent experience.
6+ years of experience building analytics pipelines in a production development environment for modeling, analysis, and reporting.
6+ years of experience coding in SQL or PySpark and Python.
6+ years of experience building and maintaining dashboards in Tableau, PowerBI, or Looker with hundreds of users.
Ability to manage projects independently and collaborate cross-functionally to distill abstract requirements into clear data products.
Experience building analytics pipelines using Snowflake SQL or PySpark and tools like Airflow and dbt (preferred).
3+ years experience managing semantic layers in tools like Cube, dbt, Snowflake, or LookML (preferred).
3+ years experience developing reusable data visualization assets like Tableau viz extensions (preferred); 3+ years of retail data experience (preferred); Master's degree (preferred).