About the company We're hiring for the go-to platform in commodity trading, the tool trading desks rely on to make pre-trade calls. - Closed a $42M Series B in February 2025 and scaling fast - Around 130 people across offices in Switzerland, London and Spain, with the Spain hub set to keep growing through 2026 - Investing heavily in AI, including a new Forward Deployed Engineer function built for enterprise clients - A lean, senior team that moves like an early-stage Stripe or Palantir: high bar, real ownership, minimal red tape Data is the backbone of that ambition. Every AI initiative and every trader-facing insight runs through the pipelines this team owns, which makes this a genuinely architecture-level seat, not just an execution role. La descripción completa del puesto cubre todas las habilidades asociadas, la experiencia previa y cualquier cualificación que se espera que tengan los solicitantes. About the role Day-to-day: - Lead pipeline architecture: Design, build and evolve scalable ETL frameworks powering real-time and analytical processing - Own platform health: Optimise for latency, throughput and reliability as data volumes scale - Bridge data and backend: Work closely with engineering and stakeholders to align infra with product and trader-facing outcomes - Drive architecture decisions:
Shape pipeline reliability, data quality and scalability across the platform - Shape target architecture: Define how data gets ingested, transformed, stored and served as the platform grows - Mentor engineers: Through design reviews, technical discussions and hands-on knowledge sharing What you'll need: - 7+ years as a data or software engineer with production-grade data systems delivered - 2+ years in a product-focused organisation, working cross-functionally - Proven track record scaling data-intensive pipelines in production - Hands-on with Flink or Spark (stream and batch processing) - Comfortable across Kotlin, Python and TypeScript - Equally sharp on high-level architecture and low-level implementation - Experience deploying data infra on AWS or GCP - Hands-on with Kafka, Redis and/or clustered Postgres Who should apply? A hands-on Staff-level data engineer who wants ownership over architecture, not just code, and who's energised by being handed a problem instead of a spec. Bonus points if you've worked with Apache Iceberg, dbt, or built data infra to support AI agents. xqysrnh Hay opciones de teletrabajo/trabajo desde casa disponibles para este puesto.