Data Solutions Engineer, Retail Customer Insights at Apple

Cupertino, California, United States -

Full Time

Start Date

Immediate

Expiry Date

18 Aug, 26

Salary

0.0

Posted On

20 May, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Data Science, Python, R, SQL, Machine Learning, NLP, LLMs, Snowflake, BigQuery, Tableau, Streamlit, Qualtrics, Medallia, Data Visualization, System Architecture

Industry

Computers and Electronics Manufacturing

Description

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. Apple’s worldwide Retail Engagement, Marketing and Merchandising (REMM) team creates and delivers programs, campaigns, initiatives, and experiences that help Apple Retail’s customers and teams discover, buy, and go further with Apple products and services. These efforts increase awareness, drive conversion, and grow affinity for Apple. Apple Retail's Customer Insights team is looking for a Data Solutions Engineer to help us build the tools and systems that transform how we listen to our customers and teams. In this role, you will bring together data science, research operations, and emerging technologies to directly impact decisions across all of Apple’s global direct channels (Apple Stores, Apple.com, the Apple Store app, and other digital platforms). As our lead architect, you will tackle complex data challenges and build the infrastructure that amplifies the reach and impact of our research. DESCRIPTION The Data Solutions Engineer will design the data infrastructure, pipelines, and machine learning workflows that power Apple Retail's research programs. By partnering closely with our team of researchers and program managers, you will help modernize how we collect, process, and share findings. Whether you are enhancing our survey systems or integrating new LLM capabilities into our analysis, your work will directly improve the speed and depth of the insights shaping Retail's strategic direction. MINIMUM QUALIFICATIONS 8+ years of experience in data engineering, data science, or a related technical field, with demonstrated ability to build and ship production-quality data solutions Proficiency in Python or R, and experience with SQL and data querying at scale (e.g., Snowflake, BigQuery) Hands-on experience building or applying machine learning and AI techniques to real-world data problems (e.g., NLP, LLMs, classification, clustering) PREFERRED QUALIFICATIONS Experience modernizing or operationalizing research or analytics workflows, including building automation pipelines and integrating AI-powered tools into existing processes Proficiency with data visualization and reporting platforms such as Tableau, Streamlit, and similar tools Exposure to survey platforms and systems (e.g., Qualtrics, Medallia) and an understanding of how survey data flows from collection through analysis Expertise applying large language models (LLMs) and generative AI, including practical experience integrating these technologies into data products or analytical workflows Familiarity with survey methodology, research concepts, and customer experience measurement (e.g., NPS, CSAT) Strong documentation skills, with experience creating system diagrams, data flow documentation, and technical specifications (e.g., using Miro, Lucidchart, or similar) Self-directed and comfortable navigating ambiguity in a fast-paced, highly matrixed environment, with the ability to manage competing priorities and adapt quickly to changing business needs Ability to tailor your communications for a variety of audience types, from technical partners to senior executives

Responsibilities

Design and build data infrastructure, pipelines, and machine learning workflows to power Apple Retail's research programs. Partner with researchers to modernize data collection and integrate AI capabilities to improve strategic customer insights.