The Team

The Market Data Platform team is responsible for the data feeds that drive research and trading processes across Man Group. Tick data is our primary source of intraday market data, and we efficiently capture and store around 5bn ticks every day from a range of L1 feeds. We rely on a mix of external vendor products for other sources of market and reference data. From these sources we create pipelines that post-process data for investment use and build tooling and applications to manage the lifecycle of raw and derived data.

 

Man Group is investing heavily in faster trading strategies and algos that require access to lower latency and higher quality sources of tick data. The Market Data Platform team is a crucial part of this initiative, ensuring we have the technical capability to capture, store, manage and deliver that data, at petabyte scale.

The Role

We are looking for an experienced engineer to join the Market Data Platform team. It is an exciting time to join the team as we extend our tick data capabilities as well as ensuring our existing sources of market data are reliable and that the technology underpinning those is fit for purpose. Your challenges in the role will be varied and might include:

• Working with real-time tick and historical data vendors and their technologies to ingest and distribute data at Man Group
• Contributing to the design of a low latency, high throughput tick data platform
• Generating high quality, intraday price datasets across multiple liquid asset classes
• Building tools for visualisation and management of datasets at terabyte scale
• Continually improving the reference data systems in use by systematic strategies
• Optimising the use of open-source technologies such as Kafka, ArcticDB and MongoDB

 

Our Technology

 

Our systems run on Linux and most of our code is in Java & Python3, using the full scientific stack: e.g. numpy, scipy, pandas, scikit-learn. We implement the systems that require the highest data throughput in Java.

 

We use RMDS/TREP and Kafka for data pipelines, ArcticDB and MongoDB for storage, Bitbucket for source control, Jenkins for continuous integration, Prometheus + Grafana for metrics collection, ELK for log shipping and monitoring, Docker for containerisation, Kubernetes for container orchestration, Airflow for scheduling, OpenStack for our private cloud, Ansible for architecture automation, and Slack for internal communication. Our technology list is never static: we constantly evaluate new tools and libraries.

 

Working Here

 

Man Tech has a small company, no-attitude feel. It is flat structured, open, transparent and collaborative, and you will have plenty of opportunity to grow and have enormous impact on what we do. We are actively engaged with the broader technology community.

• We host and sponsor London’s PyData and Machine Learning Meetups
• We open-source some of our technology including parts of our Data Platform. See https://github.com/man-group
• We regularly talk at leading industry conferences, and tweet about relevant technology and how we’re using it. See @ManQuantTech

 

We’re fortunate enough to have a fantastic open-plan office overlooking the River Thames, and continually strive to make our environment a great place in which to work. We offer flexible working, competitive compensation, a generous holiday allowance, health and other benefits. We are also committed to continuous learning and development via coaching, mentoring, conference attendance and sponsoring academic and professional qualifications.

 

Technology and Business Skills

 

We strive to hire the brightest most highly skilled and passionate technologists.

 

Essential

• Very strong technology skills
• A proponent of collaborative software engineering techniques and methods: agile development, continuous integration, code review, unit testing, refactoring and related approaches
• Proficient in Java
• Proficient on Linux platforms
• Good knowledge of one or more relevant database technologies e.g. Oracle, MongoDB
• Familiarity with a variety of programming styles (e.g. OO, functional)

 

Advantageous

• An understanding of financial markets and instruments
• Prior experience of working with financial market data, particularly tick data
• A knowledge of modern practices for data engineering and stream processing
• Prior commercial experience working with Java
• Proponent of automation and observability when building applications
• Proficient with a range of open-source frameworks and development tools e.g. NumPy /Pandas, Spark, Apache Kafka
• Experience of web-based development using modern frameworks.
• Relevant mathematical knowledge e.g. statistics, time-series analysis

Personal Attributes

• Strong academic record and a degree with high mathematical and computing content e.g. Computer Science, Mathematics, Engineering or Physics
• Intellectually robust with a keenly analytic approach to problem solving
• Self-organised and focused on delivering value to the business with relentless efforts to improve process
• Strong interpersonal skills: able to establish and maintain a close working relationship with quantitative researchers, traders and software engineering colleagues
• Confident communicator: able to argue a point concisely and deal positively with conflicting views