Data Platform Engineer

About us

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 any complex environment, enhancing the usability and safety of automated driving systems.

Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.

At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.

Make Wayve the experience that defines your career!

Portal is the cloud platform that connects Wayve to the outside world: handling data exchange with partners, surfacing AI insights, and enabling the commercial deployment of Wayve's autonomy stack to OEM partners globally. The team operates as a startup within a scale-up
: with its own infrastructure, codebase, and direct relationships with commercial partners including Uber, Nissan and other OEMs. We move fast, own our decisions, and build systems that matter.

We’re looking for a Staff Data Platform Engineer to own and lead Wayve's Data Transfer Hub project. This is a mission‑critical piece of infrastructure that will scale to transfer petabytes of sensor data per day from partner-operated vehicles around the world.

This is a hands‑on technical leadership role driving a new project 'll design and build a globally distributed hub‑and‑spoke ingestion system, working directly with data partners like Uber and Nissan. Your infrastructure is what makes Wayve's AI model training possible at scale.

• Set technical direction for the Data Transfer Hub
  , making trade-offs across reliability, throughput, cost, partner constraints, observability and operational support.
• Lead the technical design and delivery of the Data Transfer Hub project, ingesting large volumes of video, LiDAR and sensor data from global partners at up to PB/day scale.
• Design and build parallelised, distributed data transfer pipelines using Flyte for workflow orchestration, Kafka/event‑driven patterns for lifecycle tracing, and Azure for storage and transfer infrastructure.
• Build and operate a globally distributed hub‑and‑spoke data transfer model to retrieve and share sensor data at scale with partners.
• Write infrastructure‑as‑code in Terraform
  ; build pipeline logic primarily in Python
  .
• Drive cloud‑to‑cloud and cross‑cloud networking solutions (Azure primary; cross‑cloud experience beneficial).
• Work in a fast‑changing environment: requirements will evolve; high comfort with ambiguity required.

• Proven experience building and operating large‑scale data transfer pipelines at multi‑TB or PB scale.
• Experience orchestrating parallelised transfer jobs: Flyte preferred; other workflow orchestration tools (e.g. Airflow, Prefect) will be considered.
• Experience building reliable, observable data systems
  , including retry strategies, backfills, data integrity checks, lifecycle/state tracking and operational alerting.
• Strong cloud platform skills (Azure preferred); experience working with multiple cloud providers (AWS/GCP) is a strong advantage.
• Proficiency in Python and Terraform
  .
• Cloud‑to‑cloud and networking experience (e.g. blob/object transfer and storage at scale, cross‑cloud data movement).
• A product mindset
  : you think about the customer and build solutions that fix real problems, not just implement requirements.
• Comfort working in a fast‑changing environment with evolving requirements: this is a startup within a scale‑up.
• High degree of autonomy and ownership: you take responsibility for outcomes, not just tasks.

• Experience with Kafka for event‑driven transfer observability.
• Multi‑cloud experience across Azure, AWS…