Identity & Audience Platform Lead — Hybrid Paris

Vibe

Paris

Hybride

EUR 120 000 - 180 000

Plein temps

14 jours+
Générateur de candidature

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Avantages offerts par ce poste

Variable pay
Hybrid flexibility
Health insurance
Meal vouchers
Annual offsite
Tech Syncs

Résumé du poste

Vibe is seeking a staff software engineer to lead the Identity squad within the Data Platform team. You’ll own identity resolution end to end, push the algorithms forward, and set the technical direction at scale.

This player-coach role blends hands-on clustering and ML/data systems work with leadership of a small team, guiding architecture, reliability, and cost, while collaborating across teams to advance identity in a privacy-first future.

Qualifications

  • 8+ years building and operating production ML or data systems.
  • Experience leading technical work as a tech lead, staff engineer, or team lead.
  • Hands-on experience with large-scale entity resolution, clustering, or graph problems.
  • Strong distributed-systems foundations across a modern orchestrator (e.g. Dagster), distributed compute (e.g. Spark), and large-scale storage (e.g. Iceberg).
  • A track record of building evaluation frameworks and using them to drive measurable algorithmic improvements.
  • Experience managing performance and cost at genuinely large data scale.

Responsabilités

  • Set the technical direction and roadmap for identity stack end to end.
  • Design and build clustering and identity-resolution pipelines.
  • Drive cost-aware architecture decisions and scalability improvements.
  • Lead the squad's engineer and guide cross-team roadmap decisions.

Connaissances

Entity resolution
Clustering
Graph problems
Cross-functional communication

Outils

Dagster
Spark
Iceberg

Description du poste

Vibe is seeking a staff software engineer to lead the Identity squad within the Data Platform team. You’ll own identity resolution end to end, push the algorithms forward, and set the technical direction at scale.

This player-coach role blends hands-on clustering and ML/data systems work with leadership of a small team, guiding architecture, reliability, and cost, while collaborating across teams to advance identity in a privacy-first future.

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