About the company
Were hiring for the go-to platform in commodity trading, the tool trading desks rely on to make pre-trade calls.
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. Design, build and evolve scalable ETL frameworks powering real-time and analytical processing
Optimise for latency, throughput and reliability as data volumes scale
Bridge data and backend: Shape pipeline reliability, data quality and scalability across the platform
Define how data gets ingested, transformed, stored and served as the platform grows
7+ years as a data or software engineer with production-grade data systems delivered
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
A hands-on Staff-level data engineer who wants ownership over architecture, not just code, and whos energised by being handed a problem instead of a spec. Bonus points if youve worked with Apache Iceberg, dbt, or built data infra to support AI agents.