Python Developer - Data & Analytics Team - Options Market Making

Maven Securities

Greater London

On-site

GBP 60,000 - 80,000

Full time

14 days+

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Benefits offered by this job

Competitive compensation
Group Pension plan
Annual discretionary bonus
Fully catered meals
25 days’ annual leave
Private healthcare and life assurance
Cycle-to-work scheme
Monthly company events
Private Gym

Job summary

Maven Securities, based in Greater London, is looking for a skilled data engineer to design and build reliable data systems for trading. You will collaborate with traders and researchers to manage large datasets and ensure efficient data pipelines. The ideal candidate has excellent Python skills, experience with SQL, and knowledge of containerisation technologies like Docker and Kubernetes. The position offers competitive compensation and a range of benefits including private healthcare and a pension plan.

Qualifications

  • Significant experience in designing and deploying production systems.
  • Experience with handling large data sets and time series data.
  • Familiarity with data engineering practices.

Responsibilities

  • Design and build reliable data and analytics for traders.
  • Handle terabytes of exchange traffic and perform real-time transformations.
  • Conduct analyses on trading systems and pricing algorithms.

Skills

Python skills
SQL and database technologies
Business communication
Problem-solving abilities
Attention to detail
Interest in trading and finance

Tools

Docker
Kubernetes
C++ programming
React
Typescript

Job description

Maven is a market-leading proprietary trading firm deploying its own capital across discretionary, systematic, and market‑making strategies. Backed by deep expertise in trading, technology, and research, we are relentlessly focused on improving liquidity across global listed derivatives. Through advanced execution and pricing technologies, we improve how financial markets operate.

You will work alongside traders, quant researchers and other developers to help us design and build reliable, timely and accurate data and analytics for our trading and research teams. Our data pipelines handle terabytes of exchange traffic, performing numerous transformations in real-time. We perform analysis ranging from nanosecond‑level investigations on low‑latency trading systems to research on pricing algorithms and trading strategies.

Skills You Will Have
  • Excellent Python skills, with significant experience designing, developing, testing, and deploying complex and robust production systems
  • Solid experience with SQL and modern database technologies
  • Very strong business communication skills and the ability to present information clearly and concisely
  • Enthusiasm to rapidly learn new technologies and skills
  • An efficient and diligent approach with a strong attention to detail
  • The ability to solve new and unfamiliar problems quickly and creatively
  • An interest in trading and finance
Ideal Experience Would Include
  • Handling large data sets and time series data
  • Data engineering best practices for both batch and streaming data pipelines
  • Knowledge of data serialisation formats, messaging middleware, data lakehouse technologies etc
  • Containerisation and orchestration techniques (Docker, Kubernetes)
  • Modern C++ programming
  • Front end development with React and Typescript
  • Knowledge of financial markets & securities, especially equities and options

We pride ourselves on being able to rapidly deliver well‑engineered software into production. You will be able to see the impact of your work immediately and will be in a unique position to have a direct impact on trading revenue. We make extensive use of automated testing and peer code review to ensure quality and maintainability while keeping time‑to‑market short.

What We Can Offer You
  • Competitive compensation
  • Group Pension plan
  • Annual discretionary bonus
  • Fully catered breakfast, lunch and snacks
  • 25 days’ annual leave
  • Informal dress code
  • Private healthcare and life assurance
  • Cycle‑to‑work scheme
  • Monthly company events
  • Private Gym
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