Algorithmic Trading Firm
London
Total Comp up to 500k GBP
Our client is an algorithmic trading firm that actively trades tens of thousands of instruments on over eighty venues with a daily volume of almost three hundred billion USD. They partner with counterparties, exchanges, and e-trading venues globally to provide consistent liquidity in the Equity, FX, Fixed Income, Commodity & Options markets, helping market participants throughout the world obtain the best prices in the various assets classes they cover.
The Role
Our client is seeking an experienced software engineer to lead a new Data Engineering group. You will be responsible for building a new system for processing and managing daily data that is used throughout the firm, including corporate actions, fundamentals, and index membership data.
They are not trying to collect hundreds of alternative data sources; instead, the focus is on collating the data that is most critical to the firm, both now and as the business evolves, and ensuring that they have a singular, clean, easy to access, and well-integrated repository of these data. As the owner of the firm’s daily data, you will be expected to anticipate the needs of the business and ensure the normalized data schema is minimal yet sufficient.
As with all technical leadership roles at our clients firm, you can expect the majority of your role to be engineering rather than pastoral management of a team.
Essential Attributes
- You will have several years of experience working with financial data, and in particular, experience with the subtleties of corporate actions will be crucial.
- You must be a confident programmer and proficient with at least one statically typed language (Java, C++, Go, etc.). Much of the firm’s software is written in Go, and although you will need to integrate with this existing software stack, no prior Go experience is required (so long as you are willing to learn).
- You will be very comfortable with data analysis and statistics; required to ensure sufficiently clean data (for example, regressions will be required to determine the market’s effective rate of withholding tax, so some knowledge of statistics or basic machine learning would be highly beneficial).