Principal Data Engineer

Virgin Voyages is seeking a Principal Data Engineer to provide technical leadership across the data engineering landscape, focusing on data platform architecture and pipeline design. The successful candidate will play a key role in shaping technical direction and delivering scalable data solutions that support analytics and AI enablement.

Responsibilities:

• Own and evolve technical direction for the data engineering platform, including architecture, standards, and long-term platform evolution
• Design and guide the development of scalable, reliable data pipelines and platform capabilities that support analytics and AI use cases
• Contribute to the modernization and evolution of the data platform toward more scalable and managed solutions
• Define and enhance engineering standards, architecture patterns, reusable frameworks, and best practices across the data engineering function
• Improve platform reliability, observability, testing practices, and data quality across production data environments
• Partner with machine learning and related technical teams to support AI platform enablement and help shape MLOps practices where appropriate
• Support broader adoption of AI tools in engineering workflows and day-to-day productivity, including familiarity with tools such as Claude Code and Codex
• Collaborate with Data Engineering, Analytics Engineering, and stakeholders outside the core data organization to align technical solutions with business and platform needs
• Provide selective hands-on technical contribution, particularly in the establishment of foundational services, frameworks, and platform capabilities

Requirements:

• 10+ years of experience in data engineering or related data platform roles
• Demonstrated experience designing and evolving modern data platforms, pipelines, and architecture
• Strong SQL and Python skills
• Experience working across a modern data technology stack
• Experience with cloud-based data platforms and managed services
• Proven ability to operate independently and lead technical direction with a high degree of autonomy
• Strong experience improving reliability, observability, testing, and data quality within production data environments
• Experience establishing engineering standards, architecture patterns, and reusable technical frameworks
• Experience enabling AI use cases through strong data engineering foundations
• Familiarity with AI-assisted engineering workflows and tools
• Experience with GCP, including BigQuery
• Experience with dbt or other modern data transformation frameworks
• Exposure to MLOps concepts and collaboration with machine learning engineers
• Experience with DataOps practices and modern platform operating models
• Ops or DevOps knowledge
• Experience supporting adoption of AI tools for code generation and day-to-day engineering productivity
• Experience in travel, hospitality, consumer platforms, or recommendations and personalization use cases
• Strong stakeholder communication and cross-functional collaboration skills