Jobs at NielsenIQ

Design, build and maintain scalable data-test automation frameworks using Python/PySpark and SQL on cloud (Azure/Databricks). Create and execute automated and manual test suites, write test plans, validate UI and services, integrate tests into CI/CD pipelines, collaborate with cross-functional Agile teams, and provide technical guidance and tooling for monitoring and deployment.

Design, develop, and maintain native Android and React Native applications using Kotlin. Implement MVVM and Clean Architecture, follow test- and source-driven practices, debug performance and WebView issues, collaborate with UX/QA, track work in Jira, and communicate within a global team.

Build and deploy production-grade generative AI systems (LangChain, LangGraph, MCP) and architect modular Angular front-ends with microfrontend patterns. Develop Python AI pipelines, deploy on Azure (AKS, Functions, App Services), integrate observability tools, maintain CI/CD, and collaborate cross-functionally to deliver scalable enterprise solutions.

Design and implement scalable, cloud-native Python backend services and APIs (FastAPI). Integrate and fine-tune LLMs/SLMs, implement RAG and vector DB workflows, build distributed event-driven systems, apply CI/CD and DevOps practices, ensure observability and testing, and collaborate across teams to deliver AI-powered solutions.

Design, implement, test, deploy, and operate Java-based microservices. Own feature lifecycle, ensure performance and scalability, participate in design discussions, and improve system architecture and tooling.

Lead execution of data acquisition innovation initiatives: design solutions, run pilots/POCs, coordinate stakeholders (IT, DSci, Ops), deploy automation/APIs/AI tools, monitor adoption and performance, and manage innovation backlog.

Design, build and maintain scalable automation frameworks for ETL/big-data pipelines using Python/PySpark and Databricks. Perform manual and automated UI, API and service testing, develop CI/CD deployments, collaborate with cross-functional teams, and create monitoring utilities. Support test planning, debugging, and documentation for cloud-based data platforms.

Lead design and delivery of enterprise AI tools: embed with business teams, prototype LLM and agentic solutions, deploy production-grade systems in cloud environments, create reusable AI platforms, and drive adoption across global functions.

Act as the bridge between Supplier Engagement and Ops to validate, classify and improve retailer/vendor data. Perform ETL, data cleaning, KPI reporting, RCA, query resolution, productivity initiatives, and onboarding support while maintaining SAP, FTP/MFT, and transactional data integrations for large, multi-format and TLog datasets.

Lead the data ecosystem vision for the DMaaS platform, define data integration strategies, and enable clients with scalable data solutions.

Design, develop, and maintain high-performance, scalable distributed services and APIs. Own feature implementation end-to-end, write automated tests, instrument observability, participate in production support and incident analysis, perform code/design reviews, mentor engineers, and contribute to architecture and tooling decisions.

Full‑stack software engineer building and enhancing web applications: develop Java/Spring Boot backends, Angular frontends, microservices, and cloud-based solutions. Collaborate with product and architects, participate in design/code reviews, write clean code, perform end‑to‑end testing, and follow SDLC best practices.

Design, build, and operate data flows and ETL pipelines for ML; manage data versioning, CI/CD, dependency management (poetry); deploy scripts/models; use orchestrators and GCP data services.

Lead and develop a client-facing operations team, manage escalations and SLAs, perform business reviews with manufacturing clients, analyze KPIs, and collaborate with Data Operations, Data Science, and Technology to resolve and prevent issues.

Lead and develop a team handling client inquiries for manufacturing clients, ensure SLA/KPI compliance, resolve escalations, run business reviews, analyze operational data and produce performance reports, identify process improvements, and collaborate with cross-functional teams to prevent and mitigate issues.

The Associate Manager leads delivery within a region, ensuring stability while achieving client commitments. Responsibilities include quality management, cost efficiency, stakeholder collaboration, and people leadership to enhance performance and client satisfaction.

The role involves designing, building, and managing data platforms using Azure services, focusing on ETL/ELT processes and data architecture while mentoring junior engineers.

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