Staff Data Engineer | Spain | Remote

Talent-R; Mos; A distancia; EUR 70.000 - 100.000; Jornada completa

Descripción de la vacante

Talent-R in Spain is seeking a hands-on Staff-level Data Engineer to own architecture for a scalable data platform used by commodity trading teams. You will design ETL pipelines, ensure low-latency data processing, and collaborate with engineering and product stakeholders to align infra with business outcomes.

You will mentor engineers, drive architectural decisions, and contribute to selecting technologies that scale as the platform grows.

Formación

• 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.
• Experience deploying data infra on AWS or GCP.
• Hands-on with Kafka, Redis and/or clustered Postgres.

Responsabilidades

• 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.

Conocimientos

7+ years data engineering

2+ years product-focused

Herramientas

Flink

Spark

Kotlin

Python

TypeScript

AWS

GCP

Kafka

Redis

PostgreSQL

Descripción del empleo

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.

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.