Home » Senior Manager, Data Engineering - Santa Monica, 90404

Senior Manager, Data Engineering - Santa Monica, 90404 at Universal Music Group

Position Senior Manager, Data Engineering - Santa Monica, 90404
Posted 05 Aug 2026
Expired 04 Sep 2026
Company Universal Music Group
Location Santa Monica | US
Job Type Full Time

Job Description:

Latest job information from Universal Music Group for the position of Senior Manager, Data Engineering - Santa Monica, 90404. If the Senior Manager, Data Engineering - Santa Monica, 90404 vacancy in Santa Monica matches your qualifications, please submit your latest application or CV directly through the updated Jobkos job portal.

Please note that applying for a job may not always be easy, as new candidates must meet certain qualifications and requirements set by the company. We hope the career opportunity at Universal Music Group for the position of Senior Manager, Data Engineering - Santa Monica, 90404 below matches your qualifications.

Senior Manager, Data Engineering - Santa Monica, 90404, United States of America

How we LEAD:

We are seeking an experienced and driven Senior Data Engineering Manager - Enterprise Data Products within the Global Data & Analytics team.

You are passionate about leading teams that deliver scalable, reliable, and AI-ready data platforms that power enterprise decision-making, advanced analytics, and ecommerce growth. 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, semantically consistent enterprise data.

In this role, you will lead teams of data engineers responsible for delivering domain-specific data products, semantic layers, and data marts that serve as trusted, AI-ready sources of truth across the organization, while shaping how data is structured, governed, and exposed to support AI/ML use cases, feature engineering, and semantic consistency across tools and applications.

How youll CREATE:

  • Lead and manage a team of data engineers delivering enterprise-grade data products, data marts, and AI-ready data assets.
  • Lead the strategic design and delivery of scalable data pipelines and architectures that support commerce analytics, machine learning, and AI workloads.
  • Partner with Ecommerce, Product, Growth/Marketing, Finance, and Data Science stakeholders to enable AI use cases, feature stores, and model-ready commerce datasets.
  • Champion engineering best practices for AI-ready data foundations, including data quality, completeness, consistency, lineage, customer identity resolution, and trusted order/product/customer domains.
  • Lead development and implementation of semantic layers that standardize business definitions.
  • Ensure enterprise data is structured and documented to support LLMs, knowledge graphs, personalization, forecasting, and downstream AI applications.
  • Own platform reliability, including SLAs, monitoring, observability, and incident management for ecommerce analytics and AI data pipelines.
  • Lead the implementation and enforcement of data contracts and schema governance to improve stability and usability for AI and analytics consumers.
  • Lead adoption of modern data architecture patterns (lakehouse, real-time streaming, batch processing, feature stores, data monitoring, and observability).
  • Guide platform optimization for performance, scalability, freshness, and cost while supporting high-volume ecommerce data and compute-intensive AI workloads.
  • Collaborate with governance teams to ensure data is discoverable, explainable, and compliant, especially for AI use cases.
  • Mentor and develop engineering talent, fostering expertise in data engineering and AI data readiness principles.

Bring your VIBE:

  • 10+ years of data engineering experience, with 3+ years in a leadership role and direct ownership of ecommerce, digital commerce, DTC, retail, or marketplace data domains.
  • Deep knowledge of modern data architectures (lakehouse, real-time streaming, batch processing).
  • Strong understanding of data modeling, including dimensional modeling, feature engineering, and semantic layer design.
  • Proven leadership experience delivering AI-ready data platforms and ML/AI workflows, including feature stores, training datasets, model data pipelines, personalization, demand forecasting, churn/retention, attribution, and other generative AI initiatives.
  • Experience driving data quality, governance, and observability frameworks critical for AI trust and explainability.
  • Demonstrated ability to translate business, ecommerce, analytics, and AI requirements into scalable data engineering solutions.
  • Strategic exposure to AdTech and MarTech, with experience in the music/entertainment industry preferred, and the ability to connect audience engagement, marketing technology, and data-driven growth initiatives
  • Experience with cloud ecosystems (AWS, Azure, or GCP) and big data technologies (Spark, Snowflake, Databricks, etc.). GCP is a strong plus.
  • Strong leadership, stakeholder management, and cross-functional collaboration skills.
  • Awareness of data governance and privacy principles, including customer data privacy, is preferred.
  • Ability to lead effectively in a fast-paced environment, balancing priorities while maintaining quality, stakeholder alignment, and delivery discipline.
  • Ability to lead the creation of impactful executive presentations that communicate strategy, tradeoffs, roadmap decisions, and measurable business outcomes.

Job Info:

  • Company: Universal Music Group
  • Position: Senior Manager, Data Engineering - Santa Monica, 90404
  • Work Location: Santa Monica
  • Country: US

How to Submit an Application:

After reading and understanding the criteria and minimum qualification requirements explained in the job information Senior Manager, Data Engineering - Santa Monica, 90404 at the office Santa Monica above, immediately complete the job application files such as a job application letter, CV, photocopy of diploma, transcript, and other supplements as explained above. Submit via the Next Page link below.

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