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

Company Description

NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. 

Job Description

About the Role 

We are seeking a Sr. Director, Engineering to lead AI-first transformation across customer-facing SaaS product engineering capabilities. This leader will shape technical direction, drive engineering excellence, and deliver scalable, reliable, and high-impact product outcomes in a highly matrixed, globally distributed environment. 

This is a people leadership role that requires deep software engineering roots. The successful candidate will be credible with senior engineers and architects, comfortable engaging in critical system design and architecture decisions, and able to translate complex technical direction into clear product, customer, and business outcomes. 

The role is accountable for engineering delivery outcomes and technical direction while operating through senior engineering leaders, technical leaders, architects, and cross-functional partners. The ideal candidate is a constructive challenger who can question legacy assumptions, elevate engineering standards, and guide mature SaaS capabilities toward an AI-first future. 

Key Responsibilities 

AI-First Product and Engineering Transformation 

• 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. 

Engineering Strategy, Architecture, and System Design 

• 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. 

SaaS Product Engineering Delivery 

• 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. 

Production Excellence and Engineering Operations 

• 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 o