Senior Manager, Data Engineering

• 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 supporting 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 data quality, completeness, consistency, lineage, customer identity resolution, and trusted order/product/customer domains
• Lead development and implementation of semantic layers standardizing business definitions
• Structure and document enterprise data 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 implementation and enforcement of data contracts and schema governance
• Lead adoption of lakehouse, real-time streaming, batch processing, feature stores, data monitoring, and observability patterns
• Guide platform optimization for performance, scalability, freshness, and cost
• Collaborate with governance teams to ensure data is discoverable, explainable, and compliant
• Mentor and develop engineering talent in data engineering and AI data readiness principles

• 10+ years of data engineering experience
• 3+ years in a leadership role
• Direct ownership of ecommerce, digital commerce, DTC, retail, or marketplace data domains
• Deep knowledge of modern data architectures, including lakehouse, real-time streaming, and 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 generative AI initiatives
• Experience driving data quality, governance, and observability frameworks critical for AI trust and explainability
• Ability to translate business, ecommerce, analytics, and AI requirements into scalable data engineering solutions
• Strategic exposure to AdTech and Mar Tech
• Experience in the music/entertainment industry preferred
• Experience with AWS, Azure, or GCP and big data technologies such as Spark, Snowflake, and Databricks; GCP is a strong plus
• Awareness of data governance and privacy principles, including customer data privacy, preferred
• Strong leadership, stakeholder management, and cross-functional collaboration skills
• Ability to lead effectively in a fast-paced environment while balancing priorities, quality, stakeholder alignment, and delivery discipline
• Ability to create impactful executive presentations communicating strategy, tradeoffs, roadmap decisions, and measurable business outcomes

Demonstrates expertise in leading data engineering teams to deliver scalable data architectures and AI-ready data platforms, with a strong focus on data quality, governance, and compliance. Proficient in translating complex business and AI requirements into effective data engineering solutions.

• Data Engineering Leadership
• AI-Ready Data Platforms
• Data Quality Governance
• Modern Data Architectures
• Ecommerce Data Domains

• Data Modeling
• Feature Engineering
• Semantic Layer Design
• Dimensional Modeling
• Real-Time Streaming
• Batch Processing
• Lakehouse Architecture
• Machine Learning Workflows
• Data Pipeline Development
• Data Governance

• Stakeholder Management
• Cross-Functional Collaboration
• Leadership
• Strategic Communication
• Mentoring

• Ecommerce
• Digital Commerce
• DTC
• Retail
• Marketplace
• Ad Tech
• Mar Tech
• Data Privacy
• Customer Identity Resolution
• Generative AI

• AWS
• Azure
• GCP
• Spark
• Snowflake
• Databricks