Staff Data Engineer | Spain | Remote

We're hiring for the go-to platform in commodity trading, the tool trading desks rely on to make pre-trade calls.

• $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.

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.