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. 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 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.