Lead Data & AI Platform Engineer, Live Nation

• The ideal candidate combines strong technical expertise with business acumen and can independently lead complex projects that improve customer experience, operational efficiency, and AI performance
• Strong experience designing scalable data platforms, enterprise data architectures, and Databricks-based operational intelligence solutions
• Proven experience as a Data Engineer, Analytics Engineer, Data Scientist, Machine Learning Engineer, AI Engineer, or related technical leadership role
• Strong experience with Databricks, Spark, cloud data platforms, and enterprise-scale data pipelines
• Experience developing AI/ML solutions using Python and modern data science frameworks
• Strong background in statistics, machine learning, NLP, forecasting, and operational analytics
• Deep understanding of conversational AI ecosystems, intent modeling, NLU analytics, and AI performance measurement
• Experience implementing CI/CD frameworks, version control, automated testing, and DevOps best practices
• Experience building scalable dashboards and reporting solutions using BI tools and modern visualization frameworks
• Ability to independently lead complex initiatives with competing priorities and organizational visibility
• Strong communication, stakeholder management, and problem-solving skills
• You take ownership of complex initiatives and deliver results that drive meaningful business impact
• You build strong partnerships and influence outcomes across technical and business teams
• You balance strategic thinking with hands-on execution, navigating ambiguity and making sound decisions
• You provide technical leadership, coaching, and mentorship that helps others grow and succeed
• You establish scalable solutions, standards, and best practices that improve organizational capability
• You communicate clearly, build trust, and foster a culture of accountability, collaboration, and continuous improvement

Desirable

• At Ticketmaster, we are building a digital-first customer operations ecosystem powered by data, analytics, automation, and AI
• As part of the Contact Center Technology team, the Lead Data & AI Platform Engineer will play a critical role in scaling the platforms and intelligence capabilities that power customer support, automation, workforce optimization, and conversational AI across global markets
• This role is responsible for designing and scaling the data, analytics, and AI platforms that power customer operations intelligence across Ticketmaster's global support ecosystem
• The position combines data engineering, operational analytics, machine learning, and technical leadership to deliver scalable solutions that improve customer experience, automation effectiveness, operational efficiency, and business decision-making
• The Lead Data & AI Platform Engineer is expected to partner cross-functionally with Product, Operations, Engineering, Workforce Management, and AI teams to deliver data-driven insights and scalable automation solutions that support organizational goals
• Lead the design and evolution of scalable data, analytics, and AI platforms that support customer operations, automation, and operational intelligence across global markets
• Architect and optimize Databricks-based data pipelines and enterprise data platforms that unify customer, operational, workforce, and AI datasets into trusted intelligence solutions
• Drive the development of machine learning, NLP, Generative AI, and operational intelligence capabilities that improve customer experience, operational efficiency, and automation performance
• Deliver actionable insights and executive-level reporting that inform strategic decision-making and identify opportunities for operational improvement
• Establish engineering standards, governance frameworks, and best practices for data quality, platform reliability, CI/CD, and AI lifecycle management
• Partner across Product, Operations, Engineering, and AI teams to align technology investments with business objectives and long-term strategy
• Provide technical leadership, coaching, and day-to-day guidance to engineers and data scientists, supporting professional development, delivery excellence, and adoption of best practices across data, analytics, and AI initiatives