> Markdown version of [/jobs/ext/4492204-data-engineer](https://www.wearedevelopers.com/jobs/ext/4492204-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Jane Street - **Location:** United Kingdom - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Data Analysis, Computer Programming, Python (Programming Language), SQL Databases, Pandas - **Published:** November 2, 2026 - **Apply:** https://www.totaljobs.com/job/data-engineer/jane-street-europe-limited-job108268543 ## About the Role * Have strong programming skills in any language (Python a plus); you write clear, correct, and maintainable code * Proficient with SQL or DataFrame libraries like pandas or Polars * Intellectually curious with a meticulous approach to data investigation; you enjoy the detective work required to make sense of unfamiliar datasets * A clear and concise communicator * Fluency in English required ## Description We are looking for a Data Engineer to turn messy, real-world datasets into reliable inputs for research and trading. Jane Street depends on data from a wide variety of sources to understand markets and the global economy-think world news, decades of weather patterns, deidentified credit card spending, or packet captures of stock exchange market data feeds. Clean, well-structured data is the difference between noise and a profitable trading signal. You'll work closely with trading desks to identify Jane Street's data needs, evaluate datasets, and build pipelines that ingest and transform external data. You'll figure out what data means and how best to represent it. We build our own tools and software when needed, so you'll also help shape the systems you use every day. This is a collaborative role, but you'll own your work from end to end. It requires a mix of engineering, data analysis, and product sense. You'll develop deep expertise in your data domains and use that understanding to decide what's worth building next.