Talent-R , , Spain vor 2 Tagen

Staff Data Engineer | Spain | Remote

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Das ist der Job

Bonus points if you've worked with Apache Iceberg, dbt, or built data infra to support AI agents.

Darum lohnt es sich

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.

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