Senior Data Engineer, Platform

This role is with one of Dex's trusted partner companies. We work closely with their teams to truly understand their culture, goals, and what they're looking for, so we can match you with the right opportunity and give you context about the role before you commit to a process.

Dex is an AI recruiter agent that helps you run your job search. Tell Dex your stack, seniority, and what you want to build. We will manage your applications and surface other opportunities that are a fit.

The next generation of AI learns through experience, not just static datasets. This lab builds interactive, resettable digital environments where AI agents navigate software, complete tasks, fail, and improve. Data here is a fundamental input to how those AI systems and training environments get built, not a supporting analytics function.

You'll join the Platform team, a data specialisation within software engineering, not a separate analytics silo. This is end-to-end ownership: framing, architecture, implementation, and production operation for the core data problem. You won't inherit a mature platform or be handed detailed specs; you'll shape foundational systems and own the outcomes.

• Design and build scalable systems for acquiring, ingesting, and integrating large, messy, and varied datasets.
• Develop robust validation, sanitisation, and PII-removal layers to ensure data safety and quality.
• Tackle complex data problems: duplication, corruption, inconsistent formats, and provenance.
• Make critical architectural decisions across storage, reliability, observability, security, and cost.
• Ensure reliable, high-quality data availability for AI training environment engineers.

• Built and operated substantial production data systems end-to-end, owning architecture, implementation, and production behaviour.
• Strong software engineering fundamentals; deeply hands-on with code, beyond configuring tools.
• Experience with large, complex, or messy datasets (unstructured text, web, machine-generated data), and can articulate the challenges.
• Sound judgement across storage, processing, reliability, scalability, and cost; able to discuss trade-offs.
• Comfortable with cloud infrastructure and debugging complex production systems.