WHO WE ARE AND WHAT WE DO
We are a leading global market maker, using algorithmic trading and advanced technology to buy and sell securities on multiple trading venues worldwide. We provide liquidity to the financial markets, driving efficiencies for buyers and sellers.
Founded in the 1980’s, we are an ambitious, innovative company and identified early on the importance technology would play in the fast-paced evolution of trading. This entrepreneurial spirit still drives us today and can be found in all of our offices around the world.
We now operate globally from offices in Europe, the US and Asia Pacific. Our employees work closely together in multidisciplinary teams, making our success possible.
Technology – At our company, technology is not a department, it is at the heart of everything we do. Our technologists push the limits of possibility, and then look beyond. In our fast-paced environment, short feedback loops mean projects worked on in the morning can enter production the next day.
Trading – Although our traders come from many backgrounds they all have one thing in common: they are at their best solving complex problems. Their insight into global events, market shifts and pricing ensure we are trading in the right place, at the right time.
Business Support – Around the world, our business support teams are essential for sustaining our success. In our dynamic environment, we have many exciting challenges and multidisciplinary opportunities to shape our operations and make a real impact.
Our employees are our greatest asset so we give them lots of responsibility and the support they need to make a difference. Our flat structure fosters a culture of openness and collaboration, encouraging the sharing of ideas and knowledge. It makes no difference if you have been with us for three days or three years, the best idea wins.
While we work hard, we also have a lot of fun; whether solving complex challenges or in team building, leisure and sporting activities. We also enables our employees to contribute towards a better society through our foundation.
As a data engineer, you’ll build and administer data workflows in an evolving, modern big data-based environment.
- Develop and extend in-house data toolkits based in Python and Java.
- Build data pipelines using common big data tools: Hadoop, Kafka, Spark, AWS.
- Consult with traders and developers on data solutions: assist in identifying solutions which match their problem space and harmonize with our internal data platform.
- Improve the performance of financial analytics platforms built around the big data ecosystem.
WHAT MAKES IT FUN?
- We are on the cutting edge of financial applications of big data, processing terabytes of data daily for mission critical trading systems.
- We operate at the bleeding edge of technology. If something new can bring an advantage we will adopt and incorporate the new technology.
- The landscape is always changing, creating new and exciting challenges. What we focus on today is very different from what we focused on two years ago.
- We really believe in sharing knowledge and technology between the different offices. Much of our technology stack is shared globally between our offices, and we provide opportunities to travel between the regions both for personal growth and to assist where it has the biggest impact.
- Working here is a great way to gain exposure to and learn about financial markets and technology. We know from experience that a lot of people really enjoy learning about a field beyond their immediate area of expertise, it’s one of the things that makes this job more interesting than others.
- We employ a broad range of people with varying backgrounds. What they have in common is their superior technical expertise, their extraordinary smarts and their collaborative approach.
WHO YOU ARE:
- 3+ years of experience working with Hadoop, Spark, and SQL
- 2+ years of experience developing streaming data applications using Kafka
- Strong Java, SQL, and Python development skills
- Experience with common data-science toolkits, especially python-based
- Strong statistical analysis skills
- Demonstrated ability to troubleshoot and conduct root-cause analysis
- Unix scripting experience (bash, tcsh, zsh, python, etc)
- Experience with DevOps tools such as TeamCity, Gerrit, JIRA
- Experience with running code in containerized environments is a plus, especially Docker and Kubernetes
- User-focused: driven to deliver a usable product to users, rather than by technology itself