Software Developer - Risk Data Pipelines
Summary
Builds and maintains data pipelines for trade ingestion, analytics, and regulatory reporting in a quantitative hedge fund using Python and financial market data systems.
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