Job 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™.

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 explicit 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 pro

📌 Director, Engineering (Canada)
🏢 NielsenIQ
📍 Canada