Data Engineer

Bookboost

. Design and build scalable data infrastructure for hundreds of gigabytes to terabytes of guest data .

Posted 9/15/2026full-timeRemote • SwedenMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building scalable data infrastructure and pipelines, with a strong focus on AWS, PySpark, and data orchestration for machine learning and AI applications. Proven ability to own production systems and collaborate effectively with product teams to create reusable data resources.

Highest-signal resume keywords

Data EngineeringAWSPySparkData Pipeline DevelopmentMachine Learning Integration

ATS Keywords

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Hard Skills

Data Infrastructure DesignData Pipeline DevelopmentDistributed Data ProcessingData TransformationData OrchestrationQuantitative AnalysisPerformance EstimationData MovementBatch ProcessingStreaming Data

Soft Skills

Self-MotivatedStrong Sense of OwnershipPassionAmbitionGrowth Mindset

Tools & Technologies

AWS RDSECSDockerAI Tools

Industry Keywords

Data EngineeringHospitality EngagementCloud-Based Data ServicesData AnalyticsMachine Learning

Tech Stack

Tools & technologies

AWSCloudDockerPySpark

About the role

Key responsibilities & impact

Design and build scalable data infrastructure for hundreds of gigabytes to terabytes of guest data
Move, transform and make data available to the frontend application and machine learning and AI pipelines
Design and build scalable data pipelines alongside Product and Engineering
Build and deploy ingestion, transformation and storage pipelines at high scale
Monitor data pipelines end to end
Build tools and abstractions for analytics, recommendations and machine learning
Develop data orchestration and streaming pipelines
Create reusable data resources and design patterns in close collaboration with product teams
Shape the data foundation for Bookboost’s hospitality engagement platform

Requirements

What you’ll need

4+ years of industry experience in data engineering
Production systems you have owned rather than contributed to
Strong engineering skills, ideally with distributed data processing
Experience with AWS and PySpark
Strong quantitative skills and experience estimating performance at high scale
Familiarity with cloud-based data services, including AWS and RDS
Familiarity with containerised infrastructure, including ECS and Docker
Familiarity with data movement including batch, CDC, streamed and batch transformations
Daily use of AI tools for writing code, documentation and pipeline logic
Comfortable building data infrastructure that powers ML and AI features
Self-motivated, with a strong sense of ownership over systems and designs
Passion, ambition and growth mindset

Benefits

Comp & perks

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
Inclusive environment where everyone can do their best work