Senior Data Engineer

Vail Resorts is a leading company in the destination resort industry, dedicated to creating exceptional experiences for both employees and guests. They are seeking a Senior Data Engineer to architect and maintain data assets that enhance marketing analytics capabilities, collaborating closely with the marketing analytics team to improve reporting and analytics across their digital landscape.

Responsibilities:

• Architect & Scale Data Pipelines: Design, build, and maintain robust, scalable ingestion pipelines from a diverse suite of marketing sources (APIs, SFTPs, webhooks etc.), ensuring high availability and data integrity
• Optimize Core Data Assets: Develop, maintain, and tune high-performance dbt models to transform raw marketing data into production-ready analytic assets for cross-functional reporting
• Drive Infrastructure Efficiency: Audit and refactor existing data infrastructure to uncover cost efficiencies and optimize compute performance across marketing data sets
• Accelerate AI Readiness: Develop and scale semantic layers and data models specifically tailored to fuel downstream AI use cases and predictive marketing analytics
• Champion Governance & Literacy: Author comprehensive data documentation, lineage maps, and artifacts to elevate data literacy and foster a culture of self-service across the organization
• Lead Cross-Functional Partnerships: Act as the primary engineering partner to the Marketing Analytics team, translating complex business requirements into high-impact, performant data products
• Bridge IT & Engineering: Collaborate closely with IT and core Data Engineering teams to align architectural standards, bridge capability gaps, and foster a cohesive, modern data ecosystem
• Serve as a Subject Matter Expert: Act as a key technical resource for data engineering best practices, scalable architectural design, and marketing data usage
• Drive Technical Excellence & Mentorship: Act as a technical mentor to elevate the team's engineering capabilities, driving continuous skill development and championing modern best practices across analytics and engineering cohorts

Requirements:

• B.S. degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Economics, Operations Research, Engineering)
• Proven ability to write clean, modular, testable, and maintainable code
• Deep understanding of how to architect production-grade systems over one-off scripts or notebooks
• Strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services
• Hands-on experience managing and processing large-scale digital marketing datasets (log-level website, application, and paid media data) efficiently across cloud infrastructure
• Experience implementing Medallion architecture and a solid understanding of data warehouse design and schema structuring
• Expert-level knowledge of dbt (Core) for modular data modeling, including strict enforcement of schema testing, documentation, and complex dependency management
• Proficient with Git workflows (branching strategies, pull requests, code reviews) and integrating pipelines into automated CI/CD deployment workflows
• Bring intellectual curiosity, an inquisitive nature, and a desire to deepen your knowledge and continue learning
• Take responsibility to proactively advance projects, contribute to the organization, and develop the best solutions
• Take initiative to understand full scope of business problems and propose solutions ahead of being directly asked
• Explain technical concepts, risks, tradeoffs, and recommendations clearly to technical and non-technical audiences
• Work effectively cross-functionally with data scientists, data engineers, analysts, application engineers, product partners, and business stakeholders
• A graduate degree (Masters or PhD) in a quantitative field
• Deep experience with Databricks, especially Unity Catalog, Delta Lake, Databricks Workflows, job/cluster optimization, and governance
• Experience using Spark or similar distributed frameworks to build or support scalable data
• Experience with data visualization tools such as Tableau or Power BI