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🏢 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.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.