Senior Data Engineer: AI-Ready Data Platforms for Ecommerce

Universal Music Group; Philadelphia (Philadelphia County); Sur place; USD 68 100 - 153 000; Plein temps

Avantages offerts par ce poste

Medical, dental, vision

401(k) with employer match

Paid time off

Fertility coverage

Résumé du poste

Universal Music Group is seeking a Senior Data Engineer – Enterprise Data Products to join the Global Data & Analytics team in Philadelphia. You will design and operate scalable data pipelines and data products that power analytics and AI/ML initiatives, with a focus on ecommerce and Shopify data.

You will build AI-ready datasets, contribute to semantic layers, ensure data quality, and collaborate with data scientists, analysts, product and governance teams to standardize definitions and enable

Qualifications

• 5–8 years of experience in data engineering or related roles.
• Experience building data pipelines, data models, and data platforms.
• Strong experience with Shopify data is strongly preferred (orders, customers, products, fulfillment).
• Hands-on with semantic layers (dbt, LookML) and modern data stack tools.

Responsabilités

• Design and build scalable data pipelines and data products for analytics and AI/ML.
• Develop and maintain ecommerce data pipelines, with Shopify focus.
• Ensure data quality, validation, and monitoring across platforms.
• Collaborate with data scientists, analysts, governance, and product teams.

Connaissances

SQL

Python

Data pipelines

Data modeling

Data warehousing

AI/ML data prep

collaboration

Outils

dbt

LookML

Snowflake

Databricks

Spark

BigQuery

Description du poste

Universal Music Group is seeking a Senior Data Engineer – Enterprise Data Products to join the Global Data & Analytics team in Philadelphia. You will design and operate scalable data pipelines and data products that power analytics and AI/ML initiatives, with a focus on ecommerce and Shopify data.

You will build AI-ready datasets, contribute to semantic layers, ensure data quality, and collaborate with data scientists, analysts, product and governance teams to standardize definitions and enable