Jobs at NielsenIQ

Designs, implements, administers, and secures enterprise Active Directory, Entra ID, Windows Server, file services, and identity infrastructure. Provides escalation support for complex system issues, performs monitoring and troubleshooting, manages M365 dependencies, maintains documentation, supports root-cause analysis, and develops security standards and operational improvements. Collaborates with project and support teams on global infrastructure initiatives and provides training and customer communication.

Oversee large, complex technology programs from initiation through production and commercial readiness. Manage scope, milestones, dependencies, risks, financials, resource planning, release plans, and program health. Coordinate cross-functional teams across technology, product, operations, data science, marketing, sales, and client deployment. Communicate status and decisions to senior stakeholders, facilitate prioritization, ensure production readiness, and drive Agile and SAFe process compliance.

Leads architecture, technology strategy, and engineering excellence across teams. Serves as a Python subject matter expert, defining design standards and best practices, guiding complex technical initiatives, and ensuring scalable, secure, reliable solutions. Mentors engineers, conducts design and code reviews, collaborates with stakeholders, drives innovation, and oversees performance optimization, automation, testing, and continuous improvement.

Provides L2 technical support for production systems in a cloud-based environment. Responsibilities include incident and problem management, root-cause analysis, SLA adherence, service-request fulfillment, monitoring, deployment support, patching, firewall changes, documentation, automation, and stakeholder coordination. The role operates on a rotating 24/7 schedule and requires collaboration with engineering and infrastructure teams.

Designs, builds, secures, optimizes, and maintains enterprise data pipelines using Python, SQL, and Snowflake. Leads architecture, coding standards, CI/CD, DevSecOps, cloud infrastructure, and distributed data solutions across Azure, Docker, and Kubernetes. Improves pipeline quality, reliability, and cost performance; mentors engineers; leads design and code reviews; drives proofs of concept; collaborates with cross-functional stakeholders; and makes sustainable technical decisions.

Research and apply state-of-the-art machine learning techniques, primarily in NLP, to large-scale business problems. Conduct feasibility studies, analyze large datasets, develop scalable and maintainable production-grade ML solutions, and collaborate on deployment. Communicate findings to technical and non-technical stakeholders, assess real-world applicability, and contribute to team development and collaboration.

Design, develop, troubleshoot, and enhance ETL applications using Python, SQL, FastAPI, Snowflake, PostgreSQL, Airflow, and Azure. Ingest and transform data from multiple sources, build reportable data marts, create monitoring utilities, and deploy components through AI-enabled CI/CD pipelines. Collaborate with Agile teams and business stakeholders while applying data warehousing, object-oriented programming, cloud, DevOps, and microservices practices.

Lead the architecture, development, deployment, and operation of AI/ML solutions for identity and access security. Build scalable pipelines, inference services, monitoring, and MLOps capabilities using cloud platforms. Integrate anomaly detection and behavioral analytics into IAM, PAM, and secrets-management workflows. Partner with cybersecurity and engineering teams, establish applied AI security standards, influence technical roadmaps, and mentor junior engineers.

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.

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.

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.