Job description

We are UMG, the Universal Music Group. We are the world’s leading music company. In everything we do, we are committed to artistry, innovation and entrepreneurship. We own and operate a broad array of businesses engaged in recorded music, music publishing, merchandising, and audiovisual content in more than 60 countries. We identify and develop recording artists and songwriters, and we produce, distribute and promote the most critically acclaimed and commercially successful music to delight and entertain fans around the world. How we LEAD: We are seeking an experienced and driven Senior Data Engineer – Enterprise Data Products within the Global Data & Analytics team. You are passionate about building scalable, reliable, and AI-ready data platforms that power enterprise decision-making and advanced analytics. You understand that modern data platforms must not only support reporting, but also enable machine learning, generative AI, and intelligent applications through high-quality, well-governed, and semantically consistent data. In this role, you will lead teams of data engineers responsible for building and operating domain-specific data products, semantic layers, and data marts that serve as trusted, AI-ready sources of truth across the organization, with a strong emphasis on ecommerce data products and Shopify data pipelines. You will play a key role in shaping how data is structured, governed, and exposed to support AI/ML use cases, feature engineering, and semantic consistency across tools and applications. How you’ll CREATE: Design and build scalable data pipelines and data products that support analytics and AI/ML use cases. Build and scale ecommerce data products and pipelines, with particular focus on Shopify data such as orders, customers, products, transactions, fulfillment, and marketing events. Develop and maintain AI-ready datasets, ensuring high quality, consistency, and usability for downstream applications. Work with data scientists and analysts to support feature engineering, model training data, and experimentation needs. Contribute to building and maintaining semantic layers that standardize business definitions and enable consistent reporting and analysis. Implement data validation, testing, and monitoring to ensure data quality and reliability. Build and optimize data models (dimensional, curated layers) aligned with business requirements. Optimize data storage and query performance by leveraging columnar data structures and databases where applicable. Support batch and real-time data pipelines using modern data stack tools. Follow best practices for code quality, version control, and CI/CD in data engineering workflows. Collaborate with product, analytics, and governance teams to ensure data is well-documented, discoverable, and trusted. Troubleshoot and resolve data issues, ensuring minimal disruption to downstream users. Bring your VIBE: 5–8 years of experience in data engineering or related roles. Strong experience building data pipelines, data models, and data platforms. Experience working with Shopify data is strongly preferred, including Shopify orders/customers/products/fulfillment schemas Proven experience handling ecommerce data at scale, including orders, carts, customers, product/catalog, inventory, fulfillment, payments, refunds/returns, promotions/discounts, subscriptions, web/app clickstream, and marketing attribution. Preferred: experience handling Shopify data and ecommerce datasets, including ingesting, modeling, validating, and reconciling commerce data across platforms. Familiarity with AI/ML data requirements, including preparing datasets for model training and analytics. Hands-on experience working with or contributing to semantic layers (e.g., dbt, LookML, etc.). Solid understanding of data warehousing, dimensional modeling, and modern data architectures. Experience with cloud platforms (AWS, Azure, or GCP) and tools like Spark, Snowflake, Databricks, or similar. Strong SQL skills and proficiency in Python or similar language. Experience working with columnar databases or columnar storage formats (e.g., BigQuery, Redshift, Snowflake, Parquet) and optimizing query performance. Experience implementing data quality checks and monitoring. Ability to work cross-functionally and translate requirements into technical solutions. Preferred candidate location: Philadelphia, PA (Philly). Perks Playlist: Join an entrepreneurial, global organization where authenticity, boldness, creativity, connection, drive, and insight aren’t just values—they’re how we work every day. Here are some of the ways we support you along the way (and just a few of the benefits we offer): Comprehensive medical, dental, and vision coverage Including 100% coverage for out-patient in-network mental health services Fertility coverage for eligible medical plan participants Wellbeing reimbursements for fitness classes, spa treatments, meal services, travel, and so much more (up to $720/year) Student Loan Repayment Assistance and Tuition Reimbursement 401(k) with 100% immediate vesting on the first 5% of your contributions, plus an additional UMG contribution A variety of ways to prioritize much-needed time away from work including: Flexible Paid Time Off (PTO) for exempt employees 3-weeks PTO for non-exempt employees 2-weeks paid Winter Break 10 Company Holidays (including Juneteenth and Wellbeing Day) Summer Fridays (between Memorial Day and Labor Day) Generous paid parental leave for every type of parent Check out our full overview of benefits on the Perks Playlist page of the career site. Disclaimer: This job description only provides an overview of job responsibilities that are subject to change. Universal Music Group is an Equal Opportunity Employer We are an E-Verify employer in Alabama, Arizona, Georgia, Mississippi, North Carolina, South Carolina, Tennessee, and Utah. Please note, UMG is not enrolled in E-Verify in California and New York, and cannot support employment of candidates whose employer must enroll in E-Verify, for example candidates on STEM-OPT. For more information, please click on the following links. E-Verify Participation Poster: English / Spanish E-Verify Right to Work Poster: English | Spanish Job Category: Data, Analytics & Business Intelligence Salary Range: $68,100 - $179,000 The actual base salary offered depends on a variety of factors, which may include, as applicable, the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job. All candidates are encouraged to apply.

Requirements

Must-haves

We are seeking an experienced and driven Senior Data Engineer – Enterprise Data Products within the Global Data & Analytics team.
You will play a key role in shaping how data is structured, governed, and exposed to support AI/ML use cases, feature engineering, and semantic consistency across tools and applications.
Design and build scalable data pipelines and data products that support analytics and AI/ML use cases.
Build and scale ecommerce data products and pipelines, with particular focus on Shopify data such as orders, customers, products, transactions, fulfillment, and marketing events.
Develop and maintain AI-ready datasets, ensuring high quality, consistency, and usability for downstream applications.
Work with data scientists and analysts to support feature engineering, model training data, and experimentation needs.
Contribute to building and maintaining semantic layers that standardize business definitions and enable consistent reporting and analysis.
Implement data validation, testing, and monitoring to ensure data quality and reliability.
Build and optimize data models (dimensional, curated layers) aligned with business requirements.
Optimize data storage and query performance by leveraging columnar data structures and databases where applicable.
Support batch and real-time data pipelines using modern data stack tools.
Follow best practices for code quality, version control, and CI/CD in data engineering workflows.
Collaborate with product, analytics, and governance teams to ensure data is well-documented, discoverable, and trusted.
Troubleshoot and resolve data issues, ensuring minimal disruption to downstream users.
5–8 years of experience in data engineering or related roles.
Strong experience building data pipelines, data models, and data platforms.
Familiarity with AI/ML data requirements, including preparing datasets for model training and analytics.
Hands-on experience working with or contributing to semantic layers (e.g., dbt, LookML, etc.).
Solid understanding of data warehousing, dimensional modeling, and modern data architectures.
Experience with cloud platforms (AWS, Azure, or GCP) and tools like Spark, Snowflake, Databricks, or similar.
Strong SQL skills and proficiency in Python or similar language.

Nice-to-haves

Experience working with Shopify data is strongly preferred, including Shopify orders/customers/products/fulfillment schemas
Preferred: experience handling Shopify data and ecommerce datasets, including ingesting, modeling, validating, and reconciling commerce data across platforms.
Preferred candidate location: Philadelphia, PA (Philly).

Application prep

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Keywords to mirror

aimachine learningmlci/cdawsazuregcpsqlpython

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Paid Time Off

Parental Leave