Senior Manager, Data Engineering

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 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 you’ll 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