Data Engineer
Summary
Design and build the data infrastructure for a hospitality guest-engagement platform, creating scalable pipelines for ingesting, transforming, and serving guest data to the frontend and ML/AI features. Core stack includes AWS, PySpark, RDS, ECS, and Docker, with an AI-native engineering approach.
We have customers across more than 20 countries and a platform that wins on depth. As we scale, the volume and importance of our data is growing fast, and we're looking for a Data Engineer to build the infrastructure that keeps up. You'll design and build the data infrastructure that carries Bookboost from hundreds of gigabytes to terabytes of guest data, moving, transforming and making it available to our frontend application and our machine learning and AI pipelines.
This is a role with real scope. You'll work with the latest technologies on hospitality-industry-first use cases spanning both analytics and machine learning, and you'll have genuine ownership of how our data platform is designed rather than implementing someone else's blueprint.
If you want to be handed narrow tickets and left alone, this is not that job. If you want to shape the data foundation the whole product runs on, it's a good one.
What you'll own and deliver
- Scalable data pipelines and infrastructure, designed and built alongside Product and Engineering
- Data pipelines for ingestion, transformation and storage at high scale, deployed and monitored end to end
- Tools and abstractions on top of the data infrastructure for analytics, recommendations and machine learning
- Data orchestration and streaming pipelines
- Reusable data resources and design patterns, built in close collaboration with product teams
- Data engineering depth: 4+ years of industry experience, with production systems you have owned rather than contributed to
- Programming and processing: strong engineering skills, ideally with distributed data processing (AWS, PySpark)
- Scale: strong quantitative skills and experience estimating performance at high scale
- Cloud and infrastructure: familiarity with cloud-based data services (AWS, RDS), containerised infrastructure (ECS, Docker), and data movement (batch, CDC, streamed and batch transformations)
- AI fluency: our engineering team runs on an AI-native stack. You use AI tools day to day for writing code, documentation and pipeline logic, and you're comfortable building the data infrastructure that powers our ML and AI features. This is a genuine requirement, not a bonus line.
- Ownership: self-motivated, with a strong sense of ownership over the systems and designs you build.
- Remote and flexible working, from home or one of our hubs
- Real influence over the data foundation the whole product depends on
- An engineering team building new ways of working with AI rather than bolting it on
- A work environment that values your ideas, with real room for creativity and impact
- Regular team events and socials
Everyone is welcome at Bookboost
We value individuality and creativity, and we are building a team that reflects the world we serve. If you are passionate about making a difference, apply even if you do not meet every criterion.
Ready to join us?
Send us your application today. We interview on a rolling basis, so apply early.