Data Engineer, The Cruise Globe

• Strong experience as a Data Engineer in a production environment
• Solid working knowledge of Databricks as a core data platform
• Proficiency in Python and SQL (including Postgres or similar)
• Experience working with cloud infrastructure, ideally AWS
• Strong data modelling skills and a structured approach to system design
• An engineering mindset to solving complex data challenges
• Experience automating data workflows and improving system reliability
• Comfortable working in a startup environment with pace and ambiguity
• Clear, logical thinking and strong problem-solving ability
• Effective use of LLMs to support reasoning, debugging, and development through tightly scoped prompts
• This role is for someone who:
• Enjoys solving complex engineering challenges, not just building infrastructure
• Cares about structure, correctness, and long-term maintainability
• Wants to work where data is central to the product experience
• Is comfortable operating in a small, high-trust team
• Is a few years into their career and ready for more responsibility
• Enjoys not having rigidly defined work or being highly siloed
• Thrives evolving systems and incomplete information
• Doesn’t want a BI or dashboard-only position

Desirable

• We are hiring a Data Engineer to help build, scale, and maintain the data foundations of The Cruise Globe
• This role exists because our data systems have reached an inflection point. We have an exceptional volume of data and strong foundations, but the business now needs more structure, automation, and scalability to support increasingly data-heavy product features
• You will work closely with our existing senior data engineer and alongside product and engineering teams to design and operate production-grade data systems. Databricks is a foundational part of our stack, and this role will be central to shaping how it is used as the business grows
• This is not a reporting or dashboard-focused role. It is a hands-on engineering role for someone who enjoys solving complex data challenges, and building durable systems that product teams can rely on with confidence
• Success in this role is defined by:
• The product team’s ability to ship data-heavy features with confidence
• Data becoming more central to the user experience and value proposition
• A clear step-change in scalability, structure, and automation
• Reduced reliance on manual or ad-hoc data processes
• Design, implement, and maintain scalable data systems using Databricks
• Help migrate and consolidate existing data workflows into a more robust architecture
• Ensure data structures are well-modelled, consistent, and fit for long-term use
• Work closely with product and engineering teams to enable data-heavy features
• Build reliable pipelines that power user-facing statistics and insights
• Ensure correctness, performance, and consistency as product usage scales
• Building pipelines to handle and interpret large volumes of geospatial data
• Combining multiple geospatial data sources (ship tracks, port data, user locations) to deliver new insights
• Design, develop and improve algorithms handing geospatial and time series data
• Identify manual or fragile processes and automate them
• Improve the reliability and maintainability of existing data workflows
• Reduce operational overhead through thoughtful system design
• Work as part of a small, senior data function with shared ownership
• Collaborate closely with product and engineering teams day to day
• Contribute ideas and improvements rather than waiting for tightly scoped tickets