Data Engineering Tech Lead- Leading Quant-Driven Market-Maker

Oxford Knight
London
2 months ago
Applications closed

Related Jobs

View all jobs

Hybrid GCP Data Engineering Tech Lead

Engineering Manager - Data Quality & Governance

Flexible Senior Data Architect & Tech Lead

Senior Data Scientist, Payments Foundation Models

Data Engineer Manager

Graduate Data Engineer

Salary: up to £200k base + bonus

Summary

Fantastic opportunity for an experienced engineer to lead a brand-new data engineering team at this tech-savvy algorithmic trading firm. A very hands-on tech lead, you'll be building a new system for processing and managing daily data that is used company-wide (including corporate actions, fundamentals, and index membership data).

Your focus will be collating the data most critical to the business, now and in the future, to ensure there is a singular, clean, easy-to-access & well-integrated data repository. As the owner of the firm's daily data, you will be expected to anticipate the business's needs so that the normalised data schema is minimal yet sufficient.

This firm uses Go for much of their software - prior Go experience is not necessary (but you must be be willing to learn and integrate with the existing software stack as necessary).

Requirements

  • Several years of experience working with financial data; knowledge of the subtleties of corporate actions will be crucial
  • Strong and confident programmer in Java, C++, Go, or other statically typed language.
  • Solid understanding of data analysis and statistics required to ensure sufficiently clean data, and some knowledge of statistics/basic ML would be highly beneficial


NB: Please don't apply if you are a fresh graduate.

Benefits

  • Generous compensation package - you are making a direct impact on the PnL
  • Flat hierarchy, focus on teamwork, where people are rewarded on merit and excellence
  • Outstanding benefits, including onsite gym/sauna/fitness classes, extensive medical cover, and excellent professional development opportunities
  • Autonomy to work in the manner and using the software & hardware that you see fit



Whilst we carefully review all applications, to all jobs, due to the high volume of applications we receive it is not possible to respond to those who have not been successful.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Jobs

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Jobs

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.