Data Platform Lead @ Wayve
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Job Details
About Wayve
Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate complex environments, enhancing the usability and safety of automated driving systems. We embrace diversity and innovation, driving a smarter and safer future.
The Role
As the Data Platform Lead for the Wayve Portal, you will shape and scale the core data platform that underpins our SaaS product for autonomous vehicle partners. The Portal supports customer access to releases, performance monitoring, and insights from complex data flows.
Your responsibilities include:
- Defining and executing the data platform architecture and roadmap.
- Driving innovation in data pipelines and APIs for dynamic use-cases.
- Building robust systems to ingest, transform, and distribute autonomous driving data.
- Ensuring reliable data handoff to internal ML training and research.
- Integrating customer-facing dashboards, analytics, and feedback loops.
- Partnering with cross-functional teams to align data standards.
- Mentoring engineering talent and promoting technical excellence.
About You
You should have at least 5 years of leadership experience in data platforms or data engineering, with a strong background in building scalable data pipelines. Expertise in modern orchestration tools, cloud-native architectures, and data standardisation is essential. Experience with autonomous driving data and customer-facing analytics is a plus.
Work Arrangement
This is a full-time hybrid role based in our London office, combining on-site collaboration and remote working flexibility.
Key Skills/Competency
Data Platform Lead: Data pipelines, Data engineering, SaaS, Autonomous driving, Cloud-native, Kubernetes, ML integration, API development, Data standardisation, Cross-functional collaboration.
How to Get Hired at Wayve
🎯 Tips for Getting Hired
- Customize your resume: Highlight data engineering leadership experience.
- Demonstrate technical expertise: Emphasize modern data orchestration and cloud-native work.
- Showcase project successes: Detail successful data platform projects.
- Prepare for cross-functional questions: Focus on SaaS and ML alignment.