Jobs at NielsenIQ

Develop and maintain scalable data-processing systems using Oracle PL/SQL, Python, cloud technologies, and Unix scripting. Design and deploy enterprise AI and generative AI solutions, including LLM and RAG applications. Own solution architecture, optimize database performance, troubleshoot distributed AKS deployments, and implement maintainable code using modern engineering, CI/CD, Agile, and version-control practices.

Leads an engineering team delivering Java, Spring Boot, Python, REST, Flask, and Azure services. Responsibilities include people management, technical direction, sprint and PI planning, delivery ownership, code quality, CI/CD and DevSecOps maturity, production monitoring, incident response, root cause analysis, roadmap alignment, and engineer development. The manager also drives adoption of AI-assisted engineering tools and collaborates with Product, Architecture, and PMO.

Leads engineering teams and managers responsible for enterprise platforms built with Java, Spring Boot, Python, REST/Flask APIs, and Azure. Owns technical health, architecture governance, reliability, DevSecOps maturity, budgets, capacity planning, hiring, and delivery across multiple teams. Partners with Product, Architecture, PMO, and senior leadership on roadmaps and dependencies while developing engineering leaders and driving operational excellence, cost optimization, and continuous improvement.

Design, develop, test, secure, deploy, and troubleshoot scalable Java and Python services using Spring Boot, Flask, REST APIs, Azure, Docker, and Kubernetes. Build data-processing components, implement concurrency and asynchronous programming, create CI/CD pipelines, perform API integration testing, and apply security best practices. Collaborate cross-functionally, resolve production issues, and guide junior engineers through code reviews and pairing.

Provides day-to-day operational support for IAM services, including user provisioning, deprovisioning, access reviews, incident resolution, authentication troubleshooting, audit support, and compliance activities. Administers IAM tools, supports integrations and deployments, handles Level 2 and on-call escalations, maintains documentation, tracks operational metrics, and drives workflow improvements. Collaborates with cybersecurity, infrastructure, application, and business teams while mentoring junior staff.

Produces accurate recurring business reports and Excel datasets using established templates. Analyzes large datasets, applies advanced Excel formulas, pivot tables, and visualizations, meets reporting deadlines, identifies data-quality issues, and proposes process improvements. The role also requires gathering information from stakeholders and clients, communicating effectively, and supporting accurate reporting and billing processes.

Plans, executes, and oversees projects from initiation through closure, managing scope, schedules, budgets, quality, risks, dependencies, governance, and change control. Coordinates cross-functional teams and stakeholders, maintains project reporting and communications, resolves issues, supports decision-making, and ensures successful delivery aligned with user and client needs.

Lead global MLOps delivery by designing scalable software architectures, data pipelines, and machine learning solutions. Guide architecture decisions, collaborate with research, architecture, and product teams, and coordinate software delivery. Manage and mentor developers, conduct code reviews, maintain documentation, promote engineering best practices, oversee testing and CI/CD, and remain accountable for technical debt and system quality.

Develop cross-platform and native mobile applications using Xamarin, .NET MAUI, .NET, and C# for iOS and Android. Design technical solutions, understand user needs, follow test-driven development practices, troubleshoot issues, and perform root-cause analysis. Collaborate within an agile enterprise environment while supporting CI/CD integrations through Azure DevOps. Preferred experience includes cross-platform frameworks, MVVM, SQLite, performance tuning, SQL, ORM frameworks, custom SDK integration, and automated testing.

Leads a software engineering team while remaining hands-on with backend architecture, Java development, microservices, coding, testing, deployment, and technical problem-solving. Oversees delivery, team development, application performance, scalability, uptime, and engineering practices. Requires extensive backend development and management experience, with expertise in Java, Spring Boot, SQL, React, databases, and modern cloud-native technologies.

Leads global market research and business projects from initiation through completion. Responsibilities include project planning, scheduling, resource and risk management, stakeholder communication, governance, reporting, KPI tracking, and continuous improvement. The role uses Smartsheet and AI tools such as Microsoft Copilot, ChatGPT, and Gemini to improve planning, documentation, reporting, automation, and decision-making while coordinating cross-functional teams and ensuring timely, high-quality delivery.

Designs and optimizes SQL Server databases, ETL/ELT pipelines, data warehouses, dimensional models, and Power BI reporting solutions. Performs data validation, query and workload optimization, pipeline monitoring, troubleshooting, and deployment activities. Partners with stakeholders to define analytics requirements and delivers dashboards, KPIs, and scalable data solutions using Azure Data Factory, Azure Data Lake Storage, DAX, and Power Query.

Administer Workday security across HCM and adjacent modules, including role assignments, access provisioning, security configuration, troubleshooting, access reviews, and incident resolution. Maintain governance documentation, approval workflows, and audit evidence while supporting segregation of duties and control effectiveness. Participate in releases, testing, migrations, and security-related projects, partnering with technical, functional, and audit stakeholders to improve security operations and documentation.

Leads an engineering team delivering scalable full-stack and AI-enabled products. Responsibilities include setting architecture and coding standards, improving Java APIs and Angular applications, guiding AI solution development, enforcing DevSecOps and testing practices, managing technical roadmaps, mentoring engineers, overseeing delivery, optimizing cost and performance, and evaluating emerging technologies. The role is approximately 50% leadership and 50% hands-on engineering, including architecture, coding, design reviews, and technical problem-solving.

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.