Senior Manager, Data Engineering

Universal Music • New York, NY

2d • $121,500 - $200,000

About The Position

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.

Requirements

• 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.
• 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.
• 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.

Nice To Haves

• 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
• Awareness of data governance and privacy principles, including customer data privacy, is preferred.

Responsibilities

• 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.

Benefits

• Comprehensive medical, dental, and vision coverage
• 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
• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed