Director, Data Engineering

Fox Corporation•Los Angeles, CA

3d•$179,000 - $228,500•Hybrid

About The Position

Fox Corporation is seeking a Director of Data Engineering to provide technical and people leadership for strategic data initiatives supporting its Advertising Sales organization. The role leads development of scalable data solutions for Business Intelligence (BI) automation and future agent-to-agent advertising experiences. The Director will build and evolve a common context layer that brings together critical data and business context, establishing a trusted foundation for analytics, automation, and AI-powered workflows. The role partners with engineering, product, data, and business stakeholders to translate Ad Sales needs into scalable data capabilities, while leading and developing a high-performing engineering team.

Requirements

10+ years of experience in data engineering, software engineering, data platforms, or related technical roles, including 5+ years leading and developing engineering teams.
Deep technical understanding of modern data engineering architectures and experience designing and scaling enterprise-grade data platforms, pipelines, and services.
Hands-on knowledge of cloud and modern data technologies such as AWS, Databricks, Apache Spark, and related distributed data processing frameworks.
Strong understanding of data lake, data warehouse, and lakehouse architectures for structuring and serving large-scale analytical datasets.
Experience with modern data orchestration and transformation frameworks and patterns for reliable, maintainable, reusable data pipelines.
Strong understanding of data modeling, data contracts, metadata management, lineage, governance, data quality, and observability.
Experience designing data platforms that support BI, analytics, automation, machine learning, and AI-powered applications.
Understanding of how enterprise data, metadata, semantic models, and contextual information can be structured and exposed to support AI agents and agentic workflows.
Experience establishing standards for scalability, reliability, performance, security, and cost optimization across cloud-based data environments.
Strong knowledge of software engineering principles, APIs, distributed systems, and integration patterns relevant to modern data platforms.
Ability to evaluate emerging technologies, make architectural tradeoffs, and set a technical roadmap balancing immediate business needs with long-term platform strategy.
Ability to translate complex business requirements into scalable technical solutions and communicate architecture, decisions, and tradeoffs to technical and business stakeholders.
Strong people leadership skills, including experience hiring, mentoring, developing, and retaining high-performing engineering talent.

Nice To Haves

Experience working in advertising, Ad Sales, advertising technology, or media technology.
Experience building data foundations or platforms that support generative AI, agentic AI, or agent-to-agent workflows.

Responsibilities

Lead and grow a high-performing Data Engineering & BI team responsible for data platforms, pipelines, and services supporting Ad Sales.
Define and execute the technical strategy for Ad Sales BI automation, improving access to and reliability and consistency of business-critical data and insights.
Architect and build a common context layer that unifies data and business context for analytics, automation, and AI-driven experiences.
Develop trusted, reusable data foundations and context to support agent-to-agent experiences and intelligent applications.
Partner with Product, Engineering, Analytics, and Ad Sales stakeholders to identify workflow automation opportunities and improve data-driven decisions.
Establish engineering standards and best practices for data architecture, quality, governance, observability, scalability, and reliability.
Modernize and automate data workflows to reduce manual processes and accelerate actionable insights.
Provide technical direction on complex data engineering challenges while balancing business priorities and long-term platform strategy.
Recruit, mentor, and develop engineering talent and foster technical excellence, accountability, collaboration, and innovation.