Senior Manager, Data Engineering

Universal Music Group.
Los Angeles, CA, United States
4 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Microsoft Azure Batch Processing Big Data Cloud Computing Data Architecture Information Engineering Data Governance Data Mart Graph Database Data Streaming
+10 more
Feature Engineering System Availability Large Language Models Snowflake Apache Spark Data Layers Data Management Data Pipelines Automation Anywhere Databricks

Job description

Experteer Overview As Senior Data Engineering Manager, you will lead teams building AI-ready, enterprise-grade data products and semantic layers to power commerce analytics, ML workstreams, and AI-driven experiences. You’ll shape data architecture (lakehouse, streaming, batch processing), govern data domains, and expose trusted data for models and applications. You collaborate across Ecommerce, Product, Growth, Finance, and Data Science to enable feature stores, model-ready datasets, and data contracts, driving scalable, explainable AI data foundations. Compensation / Benefits * Lead a team of data engineers delivering data products, data marts, and AI-ready assets * Design and deliver scalable data pipelines and architectures for commerce analytics and AI workloads * Collaborate with Ecommerce, Product, Growth/Marketing, Finance, and Data Science to enable AI use cases and feature stores * Champion data quality, governance, lineage, and semantic consistency across domains * Develop and implement semantic layers to standardize business definitions * Ensure data is documented and suitable for LLMs, knowledge graphs, personalization, forecasting, and AI apps * Own platform reliability, SLAs, monitoring, observability, and incident management for data pipelines * Enforce data contracts and schema governance for AI and analytics stakeholders * Adopt modern data patterns (lakehouse, real-time streaming, batch, feature stores, observability) * Optimize platform performance, scalability, freshness, and cost for high-volume ecommerce and AI workloads * Collaborate with governance teams to ensure discoverability, explainability, and compliance * Mentor engineers, fostering expertise in data engineering and AI readiness principles Tasks * 10+ years in data engineering * 3+ years in a leadership role with ownership of ecommerce or retail data domains * Deep knowledge of lakehouse and modern data architectures * Strong data modeling, feature engineering, and semantic layer design * Proven track record delivering AI-ready data platforms and ML/AI workflows * Experience with data quality, governance, and observability frameworks * Ability to translate business and AI requirements into scalable data solutions * Cloud experience (AWS, Azure, or GCP) and big data tech (Spark, Snowflake, Databricks) * Cross-functional collaboration and stakeholder management skills * Awareness of data governance and privacy principles Key requirements * Comprehensive medical, dental, and vision coverage * Outpatient mental health services coverage * Fertility coverage * Wellbeing reimbursements * Student loan repayment assistance and tuition reimbursement * 401(k) with immediate vesting and employer contribution

Requirements

_ * Proven track record delivering AI-ready data platforms and ML/AI workflows * Experience with data quality, governance, and observability frameworks * Ability to translate business and AI requirements into scalable data solutions * Cloud experience (AWS, Azure, or GCP) and big data tech (Spark, Snowflake, Databricks) * Cross-functional collaboration and stakeholder management skills * Awareness of data governance and privacy principles Key requirements * Comprehensive medical, dental, and vision coverage * Outpatient mental health services coverage * Fertility coverage * Wellbeing reimbursements * Student loan repayment assistance and tuition reimbursement * 401(k) with immediate vesting and employer contribution

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