Senior Analytics Engineer, Retail Data Products

Apple Inc.; Austin, Northern (TX, KY); Hybrid; USD 140,000 - 210,000; Full time

Job summary

Apple Inc. in Austin, Texas is seeking an Analytics Engineer for Retail Store Analytics to build scalable dashboards and data products that empower store teams.

You will partner with Product Management, Data Science, Engineering, and Operations to deliver centralized dashboards and AI-driven tools—driving decision support across the business. You will own the reporting roadmap, advance BI technology, and translate complex requirements into usable data products used by hundreds of users.

Qualifications

• 6+ years of analytics pipelines in production environments.
• 6+ years of SQL or PySpark and Python coding.
• 6+ years building dashboards with Tableau, PowerBI or Looker for hundreds of users.
• Ability to initiate and complete projects with minimal guidance.
• Cross-functional collaboration with data teams to translate requirements into data products.
• Bachelor’s degree in Engineering, Data Science, Business or related field.

Responsibilities

• Enhance dashboarding and conversational BI tools for non-technical users across Retail.
• Deliver high-impact dashboards and semantic layer improvements for customer experience, staffing and operations.
• Partner with product management, data science, data engineering and operations to deliver integrated tools.

Skills

Analytics pipelines

SQL

PySpark

Python

Dashboards

Tableau

PowerBI

Looker

Cross-functional collaboration

Bachelor's degree

Education

Bachelor's degree

Master's degree

Tools

Snowflake SQL

Airflow

dbt

Cube

Job description

Apple Inc. in Austin, Texas is seeking an Analytics Engineer for Retail Store Analytics to build scalable dashboards and data products that empower store teams.

You will partner with Product Management, Data Science, Engineering, and Operations to deliver centralized dashboards and AI-driven tools—driving decision support across the business. You will own the reporting roadmap, advance BI technology, and translate complex requirements into usable data products used by hundreds of users.