Posted Oct 8, 2026

Director, Engineering

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 Director, Software Engineering to lead the engineering teams building and operating customer-facing SaaS product capabilities from our India engineering hub. This leader is accountable for the delivery, quality, and technical health of a significant part of our product engineering portfolio, and for building the engineering leadership and technical talent that sustains it.

This is a people leadership role with deep software engineering roots. The successful candidate will lead through Engineering Managers, Senior Managers, and Principal Engineers, remain credible in architecture and system design discussions, and translate product and business priorities into clear, executable engineering direction.

The role operates in a globally distributed, matrixed environment and partners closely with Product Management, Architecture, Data, Security, and Quality Engineering. The ideal candidate raises the engineering bar, improves delivery predictability and production quality, and helps move mature SaaS capabilities toward an AI-first product and engineering model.

Key Responsibilities

Engineering Delivery and Execution

Own engineering delivery outcomes for a defined set of customer-facing SaaS product capabilities, including scope, quality, predictability, and time to market.
Translate product roadmaps and business priorities into executable engineering plans, team commitments, and sequenced delivery milestones through subordinate managers and technical leaders.
Set team and department priorities, allocate engineering resources across competing demands, and manage capacity, staffing plans, and budget inputs for the area.
Balance new feature development with modernization, technical debt reduction, and continuity of existing customer commitments.
Use engineering metrics — delivery predictability, cycle time, escaped defects, change failure rate, and availability — to identify systemic issues and drive measurable improvement.
Manage delivery risk proactively, escalating with clear options and recommendations rather than surfacing problems late.

Technical Leadership, Architecture, and System Design

Provide hands-on-credible technical leadership in architecture reviews, design discussions, and critical engineering trade-off decisions across the teams in scope.
Guide the design, modernization, and operation of large-scale distributed systems, cloud-native services, APIs, and data-intensive product platforms.
Direct the identification and resolution of complex, multi-dimensional technical and operational problems, leveraging resources within and outside the immediate area.
Challenge legacy assumptions constructively and drive improvements in scalability, reliability, performance, security, maintainability, and cost efficiency.
Ensure architectural decisions in the area are documented, consistent with enterprise standards, and aligned to the longer-term platform direction set by senior engineering leadership.
Raise the standard of design discipline, code quality, and technical decision-making across the teams.

AI-First Product and Engineering Adoption

Drive adoption of AI-enabled capabilities within the product area, partnering with Product, Architecture, Data Science, and Responsible AI stakeholders.
Apply GenAI tools and AI-assisted engineering practices across the SDLC to improve developer productivity, code and test quality, documentation, and modernization throughput.
Establish practical guardrails for AI usage in engineering workflows in line with NIQ security, privacy, and data governance standards.
Evaluate AI adoption on measurable outcomes — customer value, quality, and speed — rather than on tooling activity.

Production Excellence and Engineering Operations

Ensure the capabilities in scope are designed, delivered, and operated to strong standards for reliability, availability, scalability, performance, security, and quality.
Strengthen engineering practices across CI/CD, test automation, observability, operational readiness, and incident management.
Own the operational health of the area, including on-call effectiveness, incident response, root cause analysis, and follow-through on corrective actions.
Promote a production-first mindset in which operability, supportability, resilience, and cloud cost efficiency are treated as core design considerations.

People Leadership and Talent Development

Lead, coach, and develop Engineering Managers, Senior Managers, and Principal Engineers; occasionally manage senior individual contributors directly.
Own performance management for the area, including goal setting, performance appraisals, pay review input, development planning, and succession planning.
Build the India engineering talent pipeline through hiring, onboarding, internal mobility, and targeted capability building in AI, cloud, and modern engineering practices.
Shape team structure, spans, and ownership boundaries so teams have clear accountability and sustainable workloads.
Create a culture of ownership, accountability, constructive challenge, customer focus, inclusion, and continuous learning.
Lead effectively across time zones and cultures within a globally distributed engineering organization.

Stakeholder Partnership and Influence

Partner with Product Management, Architecture, Design, Data, Security, and Quality Engineering to align on priorities, dependencies, and investment trade-offs.
Influence peers, senior engineering leaders, and cross-functional stakeholders to build consensus and adopt recommendations.
Communicate clearly with technical and non-technical audiences, translating engineering topics into business-relevant decisions, risks, and outcomes.
Represent the India engineering organization in global forums, planning cycles, and technical governance discussions.

Qualifications:

Bachelor’s degree in Computer science, Engineering, or a related technical field; advanced degree preferred.
12+ years of progressive software engineering experience, including 4+ years of formal people leadership.
Proven experience managing engineering managers and/or principal-level engineers, with accountability for a multi-team area or sub-function.
Demonstrated success delivering customer-facing enterprise SaaS products, data-intensive platforms, analytics products, or comparable large-scale commercial software.
Experience improving engineering outcomes in mature SaaS environments through modernization, technical debt reduction, quality improvement, and delivery acceleration.
Experience leading or contributing to AI-enabled product capability development within enterprise SaaS or comparable environments.
Experience working in globally distributed, matrixed engineering organizations, including partnering with teams and leaders outside India.

Technical Expertise

Strong software engineering background with practical depth in system design, distributed systems, and architecture.
Solid understanding of cloud-native architecture, scalable platform design, API design, integration patterns, performance optimization, and reliability engineering.
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 trade-offs across speed, quality, scalability, cost, security, and maintainability.
Strong command of modern software development practices, including Agile delivery, CI/CD, automated testing, observability, secure engineering practices, and production operations.

Leadership Capabilities

Track record of building and developing high-performing engineering teams and first-line leaders.
Ability to challenge the status quo constructively and bring others along through influence, clarity, and technical credibility.
Strong stakeholder management and communication skills across technical and non-technical audiences, including senior leadership.
High personal 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.
Sound judgment on people matters, including difficult performance conversations and sensitive employee situations.

Preferred Qualifications

Experience scaling an offshore or India-based engineering organization with global product ownership rather than staff augmentation.
Experience with modern AI/GenAI application patterns, orchestration frameworks, model integration, retrieval-augmented generation, or agentic workflows.
Experience in retail, CPG, consumer measurement, market intelligence, data analytics, or adjacent data-rich enterprise domains.
Background in product-led technology organizations with close partnership across Product Management, Design, Architecture, Data Science, and Security.
Experience improving engineering operating models through metrics, platform thinking, and developer productivity practices.

Additional Information:

What Success Looks Like

Delivery in the area is predictable, transparent, and aligned to committed product outcomes.
Customer-facing systems show measurable improvement in reliability, performance, quality, and speed of change.
AI-enabled capabilities and GenAI-assisted engineering practices are adopted in practical, measurable ways.
Modernization progresses without compromising reliability, security, or existing customer commitments.
Engineering managers and senior technical talent operate at a higher bar, with stronger ownership and technical judgment.
The India engineering organization is recognized as a source of end-to-end product ownership and engineering leadership.
Attrition is controlled, hiring targets are met, and the internal talent pipeline is visibly stronger.

Ideal Candidate Profile

The ideal candidate is a technically grounded engineering leader who has moved from building systems to building teams that build systems — without losing technical credibility. They can hold their own in an architecture review, and they can run a performance calibration the same week.

They have delivered customer-facing enterprise SaaS at scale, and they understand what it takes to modernize a mature platform while keeping existing customers whole. They treat AI adoption as a means to improve customer value, quality, and speed rather than as a technology trend in itself.

They are a constructive challenger: intellectually curious, self-critical, comfortable questioning legacy approaches, and skilled at bringing people along in a matrixed, globally distributed environment.

Our Benefits

Flexible working environment
Volunteer time off
LinkedIn Learning
Employee-Assistance-Program (EAP)

NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://nielseniq.com/global/en/info/niqs-ai-safety-policies/

About NIQ

For more information, visit NIQ.com

Want to keep up with our latest updates?

Our commitment to Diversity, Equity, and Inclusion

At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the https://nielseniq.com/global/en/news-center/diversity-inclusion

Bachelor's degree in computer science, engineering, or related field; 12+ years software engineering experience; 4+ years people leadership; experience with SaaS, distributed systems, cloud architecture, AI, and global engineering teams.

Key Responsibilities

leading engineering
driving modernization
developing talent

Skills & Tools

Java, Python, Angular, Azure, GenAI, CI/CD, AI

Job Details

Category: Software Development
Seniority: Senior Level
Commitment: Full Time
Workplace: Remote — Toronto, Ontario, Canada
Salary: CAD 150,000 – 176,000 / year
Languages: English

Benefits

Tuition reimbursement

About NielsenIQ

A global consumer intelligence company providing analytics and insights into buying behavior. — Industry: Research and Development

Apply Now