Senior Analytics Engineer

About the Role

Victory Live is a private equity-backed technology company that specializes in maximizing distribution and yield for live event ticket inventory. The company's comprehensive platform provides an end-to-end solution for the live ticketing industry, managing thousands of sports, theater, and live music event tickets on behalf of artists, promoters, teams, venues, and professional resellers.

The ideal candidate will have a strong technical background, with experience in building and maintaining robust ELT pipelines, designing semantic data models, and developing pipelines and data structures that support AI-powered features.

What You Will Do

• Design, build, and maintain robust ELT pipelines using tools like dbt, Snowflake, Dagster, and Azure Data Factory
• Apply AI-assisted development practices to accelerate delivery and reduce toil
• Write efficient SQL and Python code, leveraging AI coding assistants to improve velocity without sacrificing code quality or reviewability
• Build and maintain semantic data models, including fact/dimension tables, metrics layers, and reusable datasets
• Develop pipelines and data structures that support AI-powered features, including LLM context retrieval, embedding generation, and structured output ingestion
• Support BI and reporting platforms by ensuring data is well-modeled, documented, and performant
• Monitor pipelines and proactively surface data quality, reliability, and freshness issues
• Maintain clear documentation of models, transformations, and lineage
• Contribute to an internal data catalog that enables both human and AI discoverability
• Integrate third-party APIs and internal services into pipelines
• Participate in code reviews, testing, and Git-based workflows

What We Are Looking For

• 5+ years of experience in analytics engineering, data engineering, or a closely related role
• Strong SQL fundamentals and experience with data modeling concepts
• Proficiency in Python for data processing, automation, and API integration
• Hands-on experience with a cloud data warehouse, such as Snowflake
• Experience with dbt or a comparable transformation framework
• Familiarity with workflow orchestration tools or ELT services
• Demonstrated comfort using AI coding assistants as a routine part of development
• Solid understanding of data modeling concepts, including normalization, dimensional modeling, and schema design
• Strong communication skills and a bias toward documentation and knowledge sharing

Nice to Have

• Exposure to agentic or LLM-based workflows
• Experience with automated alerting and remediation patterns
• Familiarity with data governance and data quality frameworks

Benefits and Perks

• Competitive salary and benefits package
• Opportunity to work with a cutting-edge technology company
• Collaborative and dynamic work environment
• Professional development and growth opportunities
• Flexible working hours and remote work options
• Access to the latest tools and technologies
• Recognition and reward for outstanding performance

• When applying for this role, be sure to highlight your experience with AI-assisted development tools and your ability to work with large datasets.
• To stand out, create a portfolio that showcases your expertise in data modeling and pipeline development.
• During the interview process, be prepared to discuss your approach to data quality and reliability, as well as your experience with workflow orchestration tools.
• When negotiating salary, consider the company's commitment to innovation and the potential for growth and professional development.
• Be cautious of companies that prioritize short-term gains over long-term sustainability and employee well-being.
• Research the company's culture and values to ensure they align with your own, and be prepared to ask insightful questions during the interview process.