Data Engineering Intern - Build Scalable Pipelines (Seattle)

Sonos; Seattle (WA); On-site; USD 28,000 - 41,000; Full time

Benefits offered by this job

Medical/Dental/Vision Insurance

401(k) with company matching

Sick time

12 paid holidays per year

Employee discount

Job summary

Sonos is offering a Data Engineering Internship in Seattle, demanding hands-on design and construction of data features on a cross-functional team. You’ll work alongside hardware, product management, and UX to build scalable data capabilities and high-quality product datasets.

Ideal candidates are undergraduates in CS/Data Science/CE with proficiency in SQL and Python, Git, and a working knowledge of data pipelines and CI/CD workflows.

Qualifications

• Currently enrolled in an undergraduate program in CS/Data Science/CE or equivalent.
• Demonstrated proficiency coding with SQL and Python.
• Familiarity with Git/version control.
• Understanding of data development lifecycle and CI/CD concepts.

Responsibilities

• Build and maintain data pipelines to collect, transform, and process product usage, device performance, and customer interaction data.
• Develop and optimize ETL workflows using Python, SQL, and cloud-based data technologies to support scalable data processing.
• Ensure data quality and reliability via data validation, monitoring, and automated testing.
• Develop datasets and analytics to provide insights into product performance and user behavior.
• Create a semantic data layer to empower ML/AI with data and diagnostics.

Skills

SQL

Python

Git

Data lifecycle

CI/CD

Education

Undergraduate student

Tools

Tableau

Snowflake

DBT

AWS

GitHub Actions

Jenkins

Job description

Sonos is offering a Data Engineering Internship in Seattle, demanding hands-on design and construction of data features on a cross-functional team. You’ll work alongside hardware, product management, and UX to build scalable data capabilities and high-quality product datasets.

Ideal candidates are undergraduates in CS/Data Science/CE with proficiency in SQL and Python, Git, and a working knowledge of data pipelines and CI/CD workflows.