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 Requirements 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 MarTech 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 Core Competencies 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. Highest-signal resume keywords Data Engineering Leadership AI-Ready Data Platforms Data Quality Governance Modern Data Architectures Ecommerce Data Domains ATS Optimization Keywords Hard Skills Data Modeling Feature Engineering Semantic Layer Design Dimensional Modeling Real-Time Streaming Batch Processing Lakehouse Architecture Machine Learning Workflows Data Pipeline Development Data Governance Soft Skills Stakeholder Management Cross-Functional Collaboration Leadership Strategic Communication Mentoring Industry Keywords Ecommerce Digital Commerce DTC Retail Marketplace AdTech MarTech Data Privacy Customer Identity Resolution Generative AI Tools & Technologies AWS Azure GCP Spark Snowflake Databricks #J-18808-Ljbffr Jobtailor