Sr. Data Engineer

Virgin Voyages is hiring a Principal Data Engineer to set the technical direction for its data platform and modernize its architecture, pipelines, reliability, and data quality. The role also leads adoption of AI-assisted engineering practices and collaborates across data engineering, analytics engineering, and machine learning teams.

Responsibilities:

• Own and evolve the technical direction of 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
• Lead the modernization of the data platform toward more scalable, managed solutions
• Champion AI-assisted engineering across the team, driving daily use of tools such as Claude Code, Cursor, and Codex, and defining howAI-generated code is reviewed, tested, and deployed
• Design and build an end-to-end, AI-driven development pipeline for the data engineering team, connecting AI agents and tools across planning, coding, testing, code review, CI/CD, and deployment
• Define and enforce engineering standards, including version control workflows, code review practices, automated testing, and CI/CD for data pipelines and platform code
• Build and improve observability across production data environments, including monitoring, alerting, logging, and lineage
• Improve platform reliability, testing practices, and data quality across production systems
• Create reusable frameworks, architecture patterns, and best practices that the wider data engineering function can build on
• Partner with machine learning and related technical teams to support AI platform enablement and help shape MLOps practices
• Collaborate with Data Engineering, Analytics Engineering, and stakeholders outside the core data organization to align technical solutions with business and platform needs
• Contribute hands-on where it counts most, especially in building foundational services, frameworks, and platform capabilities
• All other duties assigned

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
• Hands-on, daily use ofAI coding tools such as Claude Code, Cursor, or Codex, with a track record of driving their adoption across an engineering team
• Experience designing or building AI-driven development workflows that integrate AI agents and coding tools into testing, code review, and CI/CD
• Solid software engineering practices: Git-based version control, code review, and automated testing (unit, integration, and data quality tests)
• Experience building and maintaining CI/CD pipelines for data and platform code, with familiarity with Scala, Maven, and Bitbucket Pipelines
• Strong experience implementing observability in production data environments, including monitoring, alerting, logging, and lineage
• Proven ability to improve reliability and data quality in production data systems
• Experience with cloud-based data platforms and managed services across a modern data stack
• Experience establishing engineering standards, architecture patterns, and reusable technical frameworks
• Experience enabling AI use cases through strong data engineering foundations
• Proven ability to operate independently and lead technical direction with a high degree of autonomy
• To come aboard, you must currently reside full-time in one of the following states: FL, GA, IL, NY, NC, PA, TN, and TX
• Experience with GCP, including BigQuery
• Experience with dbt or other modern data transformation frameworks
• Ops or DevOps knowledge, including familiarity with Cloud Run and Kubernetes
• Exposure to MLOps concepts and collaboration with machine learning engineers
• Experience building AI agents and agentic workflows, including Model Context Protocol (MCP) servers that connect AI tools to data platforms and internal systems
• Familiarity with LLM application patterns such as RAG, embeddings, and vector search, plus evaluating and monitoring AI systems in production
• Experience with DataOps practices and modern platform operating models
• Experience in travel, hospitality, consumer platforms, or recommendations and personalization use cases
• Strong stakeholder communication and cross-functional collaboration skills