Position: Data Platform Engineer
Company: luxoft.com
Experience required: 5y
English level: upper

Application is a multi-manager platform that invests its capital with Internal and Partner portfolio managers, primarily on an exclusive or semi-exclusive basis, across quantitative, fundamental equity and tactical trading strategies. We have created a unique structure to provide global portfolio managers with autonomy, flexibility and support to best enable them to maximize the value of their businesses.

Over the last 30 years, our client has successfully capitalized on inefficiencies and opportunities within the equity markets. We have developed and invested heavily in proprietary technology, infrastructure and risk analytics. Our portfolio exposure has expanded across the Americas, Europe and Asia as well as multiple asset classes and products.
Responsibilities:
The Data Platform Engineer will be leading, architecting and developing optimized, high throughput applications for scalable research and back testing in the cloud. The infrastructure will provide PMs with infrastructure to analyze data, back test their strategies and deploy them to production trading seamlessly.

Mandatory Skills:
• At minimum, five years of experience in C++
• Expertise with low-level implementation and systems programming
• Experience with API Design
• Experience with high volume, high availability distributed systems
• Experience implementing and deploying on the cloud
• Excellent communication skills, both written and verbal
• Ability to work under pressure handling Level 3 support issues
• Excellent communication skills, both written and verbal
• Highly skilled and analytical problem solver with logical thought processes and quantitative aptitude
• Strong ownership experience and a track record of delivering results
• A degree in Computer Science, Engineering, or a related field

Distributed Control System, C++, API, Cloud
Nice-to-Have Skills:
• Experience within a quantitative trading firm/hedge fund
• Experience with real-time market data (Thomson Reuters, Bloomberg)