Senior Director, Engineering | Retail Analytics / CPG / Market Intelligence

NielsenIQ is the world’s leading consumer intelligence company, delivering comprehensive insights into consumer behavior. They are seeking a Senior Director of Engineering to lead the transformation of customer-facing SaaS product engineering capabilities towards an AI-first model, ensuring high-impact product outcomes and engineering excellence.

Responsibilities:

• Lead the evolution of customer-facing SaaS product engineering capabilities from a mature SaaS model toward an AI-first product and engineering model
• Drive AI-enabled product innovation that improves customer workflows, decision support, automation, insight generation, and product differentiation
• Apply practical understanding of GenAI tools and AI-assisted engineering practices to improve SDLC effectiveness, developer productivity, software quality, testing, documentation, and modernization efforts
• Partner with product, architecture, security, privacy, data governance, and responsible AI stakeholders so AI-enabled capabilities are implemented thoughtfully within enterprise standards
• Define and communicate technical direction for customer-facing SaaS product engineering capabilities in alignment with product strategy, business priorities, and long-term platform evolution
• Provide deep technical leadership in architecture reviews, system design discussions, and critical engineering tradeoff decisions
• Guide the design and modernization of large-scale distributed systems, cloud-native services, APIs, data-intensive product platforms, and integrated user experiences
• Challenge existing technical approaches and identify opportunities to improve scalability, reliability, performance, security, maintainability, cost efficiency, and customer value
• Raise the engineering bar around system design, design discipline, architectural decision-making, and long-term technical sustainability
• Drive engineering delivery outcomes across complex, customer-facing SaaS product capabilities while ensuring alignment across Product, Architecture, Engineering, and Business stakeholders
• Translate product and business goals into executable engineering direction, prioritization, and delivery plans through senior engineering leaders and technical leaders
• Balance new AI-first capability development with modernization of mature enterprise SaaS systems, technical debt reduction, and continuity of existing customer commitments
• Improve measurable engineering outcomes, including delivery predictability, release quality, engineering productivity, modernization progress, and customer-impacting delivery velocity
• Contribute to planning, prioritization, resource allocation, and engineering investment tradeoff decisions in partnership with cross-functional stakeholders
• Ensure customer-facing SaaS capabilities are designed, delivered, and operated with strong standards for reliability, availability, scalability, performance, security, and quality
• Strengthen engineering practices across CI/CD, test automation, observability, operational readiness, incident learning, and continuous improvement
• Promote a production-first mindset that treats operability, supportability, resiliency, and cost efficiency as core design considerations
• Use engineering metrics and operational signals to identify systemic issues, improve team effectiveness, and guide technical and organizational improvements
• Lead through direct leadership accountability, senior technical credibility, and matrixed influence across Engineering, Product, Architecture, Business, and enabling functions
• Develop and mentor Directors, Senior Managers, Principal Engineers, and senior technical talent, building leadership capacity and raising the technical bar across teams
• Create a culture of ownership, accountability, constructive challenge, customer focus, innovation, and continuous learning
• Align globally distributed teams across time zones, cultures, and organizational boundaries
• Communicate clearly with executive, technical, and non-technical audiences, translating complex engineering topics into business-relevant decisions and outcomes

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related technical field
• 15+ years of progressive technology and software engineering leadership experience
• Proven experience leading and developing senior engineering leaders and technical leaders, including Directors, Senior Managers, Principal Engineers, or equivalent roles
• Demonstrated success leading engineering for customer-facing enterprise SaaS products, data-intensive platforms, analytics products, or comparable large-scale commercial software platforms
• Experience driving engineering transformation across mature SaaS environments, including modernization, technical debt reduction, quality improvement, and delivery acceleration
• Current experience leading AI-enabled product capability development within enterprise SaaS or comparable commercial software environments
• Experience applying GenAI tools and AI-assisted practices within engineering workflows to improve software delivery, quality, developer productivity, or modernization outcomes
• Experience leading globally distributed engineering teams in a matrixed organization
• Deep software engineering background with strong system design, distributed systems, and architecture experience
• Strong understanding of cloud-native architecture, scalable platform design, data-intensive systems, API design, integration patterns, performance optimization, reliability engineering, and enterprise architecture principles
• Prior hands-on engineering experience and leadership familiarity with technologies used by modern SaaS teams, including Java, Python, Angular, Azure cloud services, and AI/GenAI technologies and frameworks
• Ability to evaluate architectural options, challenge design assumptions, and guide technical tradeoffs across speed, quality, scalability, cost, security, maintainability, and customer impact
• Strong understanding of modern software development practices, including Agile delivery, CI/CD, automated testing, observability, secure engineering practices, and production operations
• Transformative mindset with the ability to move teams from established SaaS operating models toward AI-first product and engineering approaches
• Ability to challenge the status quo constructively, challenge self and teams to improve, and bring others along through influence, clarity, and technical credibility
• Strong executive presence, stakeholder management, and communication skills across technical and non-technical audiences
• High accountability for engineering outcomes, customer impact, and business-aligned execution
• Ability to operate effectively in ambiguity, make decisions with incomplete information, and create alignment across competing priorities
• Strong coaching and talent development skills, with a track record of building high-performing engineering leadership teams
• Experience leading AI-driven product transformation initiatives that created measurable customer value or commercial impact
• Experience with modern AI/GenAI application patterns, orchestration frameworks, model integration, retrieval-augmented generation, agentic workflows, or AI-enabled analytics experiences
• Experience in retail, CPG, consumer measurement, market intelligence, data analytics, or adjacent data-rich enterprise domains
• Background working in product-led technology organizations with close partnership across Product Management, Design, Architecture, Data Science, Security, and Business stakeholders
• Experience improving engineering operating models through metrics, platform thinking, engineering productivity practices, and production excellence