Senior Manager, Data Engineering

Jobtailor; Santa Monica (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Jobtailor is seeking a senior data engineering leader to direct a team delivering enterprise-grade data products and AI-ready assets for ecommerce analytics. You will design scalable pipelines and lakehouse architectures, partnering with Ecommerce, Product, Growth, and Finance to enable AI use cases and model-ready datasets.

You will champion data quality, governance, and observability, while guiding semantic layer design and data contracts.

Qualifications

• 10+ years of data engineering experience.
• 3+ years in a leadership role.
• Direct ownership of ecommerce/digital commerce data domains.
• Deep knowledge of lakehouse, real-time streaming, and batch processing.
• Strong data modeling including dimensional modeling and feature engineering.
• Proven leadership delivering AI-ready data platforms and ML workflows.
• Experience with data quality, governance and observability.
• Ability to translate business/AI requirements into scalable solutions.
• Exposure to AdTech/MarTech; experience in music/entertainment industry preferred.
• Experience with AWS/Azure/GCP and big data tech (Spark, Snowflake, Databricks).
• Awareness of data governance and privacy principles; leadership in fast-paced environments.

Responsibilities

• Lead and manage a team of data engineers delivering enterprise-grade data products and assets.
• Design and deliver scalable data pipelines and architectures for analytics and AI workloads.
• Partner with stakeholders across Ecommerce, Product, Growth, Finance, and Data Science.
• Champion data quality, lineage, and governance across domains.
• Lead development of semantic layers and standardized business definitions.
• Structure data to support LLMs, knowledge graphs, personalization, and AI apps.
• Own platform reliability, SLAs, monitoring, and incident management for data pipelines.
• Enforce data contracts and schema governance; promote lakehouse and real-time patterns.
• Guide platform optimization for performance, freshness, and cost; ensure compliance.

Skills

Leadership

Stakeholder Management

Cross-functional Collaboration

Mentoring

Strategic Communication

Data Modeling

Feature Engineering

Semantic Layer Design

Dimensional Modeling

Data Governance

Data Quality

Presentation Skills

Tools

AWS

Azure

GCP

Spark

Snowflake

Databricks

Job description

• 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