Lead Data Architect

This engineering-first, developer-architect role owns the technical design of Azure-first data and AI platforms, defining reusable patterns and reference architectures. The Lead Architect will spend 70-80% of their time designing solutions, building and packaging reusable patterns, and prototyping new concepts in code, with the remaining time in client-facing advisory. This role requires production fluency with Terraform, deep Azure data platform experience, and hands-on AI solution design including RAG and agentic workflows.

This senior principal role designs and architects the enterprise data platform, focusing on scalability, reliability, and integration with cloud services. The architect will define technical standards and collaborate with data engineering teams to support analytics and AI initiatives.

This senior lead role designs and oversees the data engineering architecture, building scalable pipelines and data models, requiring deep expertise in big data technologies and cloud platforms, and leads a team of engineers to deliver high-quality data solutions.

This role analyzes and optimizes LinkedIn's infrastructure operations, using large datasets to develop metrics and provide insights that improve efficiency and reduce costs. The analyst collaborates with engineering teams to drive operational excellence and support data-driven decision-making.

The Coordinator of Client Services supports the ad sales team by managing client relationships, trafficking campaigns, and resolving operational issues. This role ensures seamless execution of advertising campaigns across ESPN's linear and digital platforms.

This Media Coordinator role supports media planning and campaign operations within a media/advertising organization. Responsibilities likely include coordinating ad trafficking, managing schedules, and supporting sales or marketing teams. Requires strong organizational skills and attention to detail.

This intern role supports quality operations and system auditing processes, focusing on monitoring and improving operational quality standards. Responsibilities likely include data collection, audit preparation, and process documentation to ensure compliance and efficiency.