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# Executive Vice President, Data Engineering

- **Company:** Publicis Groupe
- **Location:** New York, NY, United States
- **Salary:** $180,215.0
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Software Quality, Information Engineering, Distributed Systems, Cloud Services, Data Strategy, Data Management
- **Published:** October 30, 2026
- **Apply:** https://www.disabledperson.com/jobs/76290227-executive-vice-president-data-engineering

## About the Role

* 15+ years of relevant technology experience, including substantial executive leadership of data or engineering organizations and experience leading senior leaders.
 * Executive experience in media, advertising technology or other data-intensive businesses; leadership across global or matrixed organizations; and scaling AI and data capabilities through internal teams and strategic partners.
 * A track record of setting enterprise data strategy and delivering complex, multiyear transformation across multiple teams, business units or markets.
 * Deep technical judgment across cloud data platforms, distributed systems and enterprise architecture, with the credibility to guide senior engineers and challenge major investment decisions.
 * Demonstrated leadership of AI-assisted engineering adoption, with measurable gains in productivity, software quality or operating efficiency and clear accountability for responsible use.
 * Experience owning material budgets, strategic partnerships and organizational change; strong executive communication and commercial judgment. A relevant degree or equivalent practical experience.
 * How you work with AI
 * Maintain practical fluency with AI tools and agents; evaluate their capabilities directly and set evidence-based expectations for adoption, verification and value.
 * Develop leaders who embed AI into engineering practices, protect confidential information and sustain technical ownership as automation expands.

## Description

* Set the data engineering strategy and investment roadmap, aligning architecture and platform capabilities with enterprise growth and business priorities.
 * Build and lead an organization of engineering leaders and teams; own organizational design, leadership hiring, succession planning and performance accountability.
 * Establish enterprise architecture principles and standards that enable reusable data products, consistent information and scalable adoption of analytics and AI.
 * Lead the function's adoption of AI-assisted engineering and agent-based automation, setting an operating model that improves delivery capacity, quality and unit economics.
 * Own the engineering operating model, including service performance, resilience, security and risk management, with clear accountability across internal teams and strategic partners.
 * Own budgets, workforce planning and strategic vendor relationships; make build-versus-buy decisions based on business value, total cost and long-term flexibility.
 * Represent data engineering in executive planning and governance; resolve cross-functional tradeoffs and hold teams accountable for measurable business outcomes and adoption.