Jobs at NielsenIQ

Leads the global technology strategy and roadmap for Consumer Panel Services. Oversees scalable data integration, processing, analytics platforms, cloud transformation, governance, security, compliance, and incident response. Partners with Product, Operations, Data Science, Architecture, and enterprise technology teams while mentoring engineering staff and driving Agile, DevSecOps, and continuous innovation. The role requires enterprise data engineering leadership, distributed computing expertise, and experience with cloud-native platforms and big-data technologies.

Develop scalable backend microservices, REST APIs, web applications, and web scraping pipelines using Python and PHP. Build crawlers for dynamic websites, optimize asynchronous and concurrent extraction, and manage PostgreSQL schemas and queries. Troubleshoot production issues, maintain system stability, and collaborate with Product, QA, DevOps, and engineering teams. The role requires expertise in Python scraping libraries, browser automation, PHP CodeIgniter, PostgreSQL, microservices, and RESTful API development. Cloud, DevOps, containerization, Git, observability, and Agile experience are preferred.

Support governance, analysis, validation, remediation, and continuous improvement of ServiceNow CMDB data. Maintain configuration items, relationships, service mappings, and integrations; monitor data quality and lifecycle controls; produce health dashboards, reports, and KPIs; support audits and compliance checks; and collaborate with infrastructure, security, application, and service teams to improve configuration management.

Develop and maintain responsive web applications with React.js, build reusable UI components, translate designs into pixel-perfect code, integrate REST APIs and third-party services, optimize performance, troubleshoot issues, and ensure accessibility, cross-browser compatibility, code quality, and scalability. Collaborate with product managers, designers, and backend developers in an Agile/Scrum environment.

Administers Workday security roles, access provisioning, security configuration, incident resolution, access reviews, and governance documentation. Supports audits by preparing evidence and validating controls. Partners with technical, functional, and audit stakeholders on security impacts, testing, controlled migrations, Workday releases, and continuous improvement across enterprise HCM environments.

Develop and apply machine learning innovations, primarily for NLP, to large-scale business problems. Conduct feasibility studies, analyze data, evaluate real-world applicability, and build scalable, maintainable, reproducible ML solutions. Collaborate on deployment and integration, communicate findings to technical and nontechnical stakeholders, understand business requirements, and contribute to team development and collaboration.

Own the cross-domain data and AI product roadmap for a reference and master data platform. Lead source and market onboarding, data-quality standards, reconciliation, AI enrichment and matching use cases, backlog prioritization, user stories, acceptance criteria, testing, SQL validation, UAT, governance, and rollout decisions. Align Process Owners, Solution Owners, Program Managers, Data Science, and Engineering while measuring data coverage, quality, and AI adoption.

Leads a software engineering team while remaining hands-on with backend architecture, coding, design reviews, testing, deployment, and technical problem-solving. Develops scalable Java microservices, guides system architecture, oversees product feature lifecycles, and ensures application performance, uptime, security, and code quality. The role also manages talent development, stakeholder relationships, agile planning, delivery oversight, and adoption of AI-assisted development tools.

Oversee and develop team members, ensure compliance with processes, enhance operational excellence, and engage stakeholders to resolve issues.

Lead design, implementation, and optimization of enterprise multi-cloud architectures across Azure, GCP, and AWS. Drive IaC, CI/CD automation, cost optimization, security compliance, high availability, and disaster recovery. Troubleshoot complex distributed systems, mentor teams, and influence enterprise cloud strategy and governance.

Design, build, and maintain automated test frameworks and suites for UI, API, and backend layers using Python/Java, Playwright/Selenium, TestNG, and SQL. Execute manual and automated tests, integrate tests into CI/CD pipelines, deploy via DevOps tools, and collaborate with cross-functional Agile teams to improve quality and monitoring.

Design, build, and optimize cloud-native AI applications using Python and distributed systems. Develop backend services, APIs, CI/CD pipelines, and Generative AI solutions (LLMs/SLMs), implement data validation and business-rule engines, integrate vector search/RAG, fine-tune models, and monitor performance with observability tools while collaborating across teams.

Lead and oversee a team of program managers delivering large, complex, cross-functional technology and business transformation programs. Drive portfolio governance, strategic planning, financial stewardship, stakeholder engagement, and organizational change to ensure measurable business outcomes and successful enterprise-wide deployments across global teams.

Design, build and maintain scalable automation frameworks and test suites for cloud/big-data systems. Implement automated and manual tests across UI, services, APIs and performance; deploy via CI/CD; collaborate with cross-functional teams and provide technical guidance.

Research, evaluate, and apply state-of-the-art ML (primarily NLP) techniques to large-scale business problems. Perform feasibility studies, EDA, and develop production-quality, scalable, reproducible ML solutions. Communicate results to stakeholders, collaborate on deployment, maintain high code and data quality, and contribute to team building and cross-functional integration.