Data Engineer - DMP, Streaming & Analytics

About the role

A lean, senior team is building a highly resilient advertising platform using an AI-first development paradigm. This role owns the data and DMP layer end to end: the event streams flowing in, the segment and audience computation, and the analytical stores that feed targeting and reporting. The work is hard, at real-time scale, and the candidate is expected to bring their own approach.

Key responsibilities

• Own the ingestion and processing pipeline, which is designed to be stream-first and kept that way rather than falling back to batch.
• Own how raw signals become targetable audiences: how they are computed, stored, refreshed and exposed to the serving path.
• Specify work as explicit, self-sufficient issues, direct agentic tooling to implement it and gatekeep every change.
• Document schemas, data contracts and architecture decisions; if it is not written down, it does not exist.

Required profile

• 5+ years building data or backend systems in production, with genuine ownership of a pipeline's reliability and output correctness.
• Experience with hard data problems where scale, real time or accuracy made the design non-obvious, able to explain the trade-offs chosen.
• Streaming experience and a real grasp of stream-vs-batch trade-offs, event modelling and schema evolution.
• Comfort in a compiled systems language; the codebase is Rust, and data thinking is valued more than the language.
• Working knowledge of an analytical data store and SQL; DMP, ad-data or audience/segmentation experience is a strong plus.
• Ability to edit and validate AI-produced code, and to decompose ambiguous goals into specifications an agent can execute unattended.
• Exceptional written communication and effectiveness in a distributed, async environment (Paris timezone +/- 3h).

Required skills

• Event streaming and stream processing, relational and analytical stores
• Rust (compiled systems language)
• SQL and an analytical data store
• Distributed and complex systems