Executive Director ME&I

VML•Detroit, MI

2h•$155,000 - $390,000•Hybrid

About The Position

We’re seeking an Executive Director of Data Engineering to lead the architecture, infrastructure, and engineering standards that power our global marketing intelligence capabilities. Reporting directly to the Chief Marketing Intelligence Officer, this leader will modernize our AI infrastructure, accelerate how we build and deliver, and set global data standards across every domain we touch — creative, CX/site, CRM, audience, and media data. The ideal candidate is a hands-on technologist and a strategic leader who can build best-in-class engineering practices at global scale while driving the move toward agile, automated, and AI-native data delivery.

Requirements

20+ years of experience in data engineering, data architecture, or platform engineering, including senior leadership of global or distributed engineering teams.
Deep expertise in modern data infrastructure, cloud platforms, and AI/ML engineering, with hands-on command of scalable pipeline and platform design.
Proven success establishing data taxonomies, standards, and governance frameworks across complex, multi-domain environments.
Experience modernizing engineering practices toward automation, agile delivery, and AI-assisted development.
Strong understanding of marketing and media data domains — creative, CX/site, CRM, audience, and media — ideally within automotive, broader industry, or agency/media agency contexts.
Track record of integrating AI responsibly and at scale, with fluency in MLOps, DataOps, and data governance.
Exceptional leadership, communication, and stakeholder-management skills at the executive level.

Responsibilities

Design and evolve scalable AI and data infrastructure that supports predictive, prescriptive, and generative use cases across the function.
Establish standards and tooling for accelerated delivery and faster coding — including AI-assisted development, reusable components, and automation that compresses time-to-value.
Evaluate and introduce new technologies that enable innovation across creative, CX/site, CRM, audience, and media data domains.
Mature our MLOps and deployment practices so models and data products move from prototype to production reliably and repeatably.
Develop comprehensive, future-proof data taxonomies and data standards that bring consistency and interoperability across domains and regions.
Set and govern global data standards — architecture, quality, lineage, documentation, and metadata — that scale across the network and agency partners.
Embed data governance, privacy, and security by design, ensuring compliance with global regulatory requirements (e.g., GDPR, CCPA) and responsible AI practices.
Create a single, trusted foundation for data that improves accuracy, accessibility, and reuse across teams.
Drive continuous progress toward agile, automated, and effective data delivery, embedding DevOps/DataOps practices and CI/CD across engineering workflows.
Define and uphold best-in-class standards for AI integration, from data pipelines through model deployment and monitoring.
Build and lead a high-performing, globally distributed engineering organization, raising the bar on technical excellence, velocity, and reliability.
Partner with product, analytics, and agency teams to ensure infrastructure and standards translate into faster, higher-quality outcomes.