Bookboost·7 days ago
7 days ago
Data Engineer
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What you'll do
- 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
What they're looking for
- 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.
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Bookboost
Sweden
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