Software Developer - Risk Data Pipelines

Position Overview: Risk Technology develops core services and systems required by Squarepoint’s systematic and quantitative trading strategies, such as real-time risk controls, position/inventory/P&L monitoring, internal order routing, and various pre and post-trading services. Risk Data Pipelines develops software on top of the core Risk Technology platform to handle market or asset-class specific processing, including: • Trade Data Ingress - Normalize and stream trade data to Squarepoint's systems from trading platforms like Bloomberg, Fidessa and SpiderRock. • Trade Data Egress - Feeds to 3rd party platforms to ensure trade booking correctness and regulatory compliance. • Services and analytics used by investment and quant teams to understand Risk exposure, P&L and to improve capital efficiency. • Automation of trading operations to support the growth of the business, such as the management of options & future expiry and automated trade, position and P&L reconciliation. This role provides an opportunity to learn many aspects of the way hedge funds operate through close collaboration with trading and quantitative teams, and as a developer you will: • Design, develop and deliver high quality and maintainable business critical software. • Work closely with stakeholders and colleagues to capture requirements, define architecture and technologies, identify and resolve bottlenecks, and deliver functionality. • Lead and contribute to design discussions and mentor other team members. • Participate in level 2 support. Required Qualifications: • Bachelor’s degree in computer science or related subject. • 4 years’ minimum Python experience working in the financial industry. • Team player with excellent communication skills. • Experience with database management systems and related technologies such as SQL. • Knowledge of traded financial instruments (Equity, FX, Credit or Rates). Nice to Have: • Experience of FIX protocol • Experience developing in data engineering (using Python with pandas, R, Julia) • Experience with KDB+/q