Data Architect (AI)

TL;DR

Data Architect (AI/Databricks): Designing and optimizing a global enterprise data platform with an accent on AI-ready data models and agent-consumable architectures. Focus on building scalable Lakehouse architectures, automating data pipelines with AI agents, and implementing robust data governance at scale.

Location: Work From Home - Must be based in California or Texas

Salary: $136,000 - $170,000 USD

Company

The world’s leading live entertainment company, comprising Ticketmaster, Live Nation Concerts, and Live Nation Media & Sponsorship.

What you will do

• Design and evolve Databricks Lakehouse architecture with a focus on scalability, cost efficiency, and AI-readiness.
• Implement a tiered data ecosystem to transform raw data systematically into refined, analytics-ready data.
• Develop conceptual, logical, and physical data models optimized for AI consumption and agent usage.
• Establish and enforce standards for metadata, lineage, and data quality across the enterprise ecosystem.
• Collaborate with engineers and stakeholders to design trustworthy, AI-automated data solutions.
• Mentor engineering staff and lead workshops to promote data literacy and architectural best practices.

Requirements

• 10+ years of tech industry experience, including 5+ years architecting big data strategies.
• 5+ years of expertise with cloud-based platforms such as Databricks, AWS, Snowflake, or Spark.
• 1+ year of experience with AI orchestration, automated modeling, or AI-enabled data engineering.
• Deep knowledge of data modeling (3NF, dimensional/star schema), medallion architectures, and ETL processes.
• Experience with Confluent Kafka for real-time data processing and API platforms.
• Must be based in California or Texas.

Culture & Benefits

• Full remote work flexibility within specified US states.
• Opportunity to drive architectural transformation and influence decisions from day one.
• High-impact role building the backbone of data for a global entertainment leader.
• Engagement with cutting-edge AI agents and automated data engineering patterns.