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Staff Data Engineer

Sparta Commodities
CompanySparta Commodities
CategoryEngineering
LocationLondon
RemoteHybrid
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted25 Jun 2026
Last verified30 Jul 2026
SourceEmployer career page (ashby)
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Description
We Are Sparta Sparta is the next-generation commodity trading platform. We give trading desks the clarity, control, and collaboration they need to move faster and trade smarter. In February 2025, we secured $42 million in Series B funding. Now we’re scaling up across the business, and it’s an exciting time to join. Our people are the driving force behind everything we do. At Sparta, you’ll be trusted to take ownership, backed by a team who wants you to succeed. You’ll be challenged, supported, and given room to grow. Because building something this ambitious takes everyone at their best. At Sparta, your work has reach. From improving our platform, to powering smarter decisions for our customers, to changing how commodity trading is done around the world. And because we’re growing fast, you won’t just build your career. You’ll accelerate it, with a level of ownership and impact you simply don’t get at bigger, more bureaucratic companies. Staff Data Engineer At Sparta, we're on a mission to build the next generation of commodity trading platforms - replacing the fragmented tools traders depend on with a single, powerful dashboard. Our product is a data-driven platform that aggregates real-time feeds from across the commodities domain, transforming them into intuitive, actionable visualisations within one unified interface. Users can explore pre-built data views or build their own custom formulas - turning raw market data into decisions. At the heart of Sparta is a serious data engineering challenge. We're building a platform that enables the rapid development of reliable, scalable ETL pipelines - the foundation everything else depends on. As our data volumes grow and our product ambitions expand, the demands on that infrastructure grow with them. We're looking for experienced data engineers who are familiar with these challenges at scale — people who understand what it takes to keep a data platform performing as complexity increases. We want people who thrive with ownership. At Sparta, you'll be handed problems, not solutions - and we expect you to run with them. Speed matters, autonomy is real, and we'd rather you move fast and course-correct than wait for permission. As a Staff engineer, you'll also be shaping the direction of the platform itself: engaging directly with stakeholders, contributing to product thinking, and investing meaningfully in the engineers around you. This role can be based in the UK (London) or Spain (Barcelona, Madrid), and we would expect to spend some time together with the team in-office (2 -3 days a week). CORE RESPONSIBILITIES - Play a leading role in the design, build, and ongoing evolution of scalable data pipelines and ETL frameworks that power both real-time and analytical data processing. - Take shared ownership of the health and performance of our data platform - optimising for latency, throughput, and reliability at scale. - Collaborate closely with engineering and cross-functional stakeholders to ensure data infrastructure aligns with product goals and trader-facing outcomes - acting as the connective tissue between data and backend engineering. - Drive architectural decisions across our data platform, with a focus on pipeline reliability, data quality, and scalability. - Contribute to the definition of our target architecture - shaping how we ingest, transform, store, and serve data as the platform evolves. - Mentor and support other engineers through design reviews, technical discussions, and hands-on knowledge sharing. SKILLS & EXPERIENCE - 7+ years of experience as a data or software engineer, with a strong track record of delivering production-quality data systems. - 2+ years working within a product-focused organisation, collaborating closely with cross-functional teams. - Proven experience building and scaling data-intensive pipelines and platforms in production environments. - Deep understanding of stream and batch processing fr
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