Python Engineer – Enterprise Trading Platform

Business Integration Partners (BIP) is Europe’s fastest growing digital consulting company and are on track to reach the Top 20 by 2030, with an expanding global footprint in the US (New York, Charlotte, Chicago, and Houston). Operating at the intersection of business and technology we design, develop, and deliver sustainable solutions at pace and scale creating greater value for our customers, employees, shareholders, and society.

BIP specializes in high-impact consulting services across multiple industries with 6,000 employees worldwide. Our domains include Financial Services business serves Capital Markets, Insurance and Payments verticals, supplemented with Data & AI, Cybersecurity, Risk & Compliance, Change Management and Digital Transformation practices. We integrate deep industry expertise with business, technology, and quantitative disciplines to deliver high-impact results for our clients.

BIP is currently expanding its footprint in the United States, focusing on growing its Capital Markets and Financial Services lines. Our teams operate at the intersection of business strategy, technology, and data to help our clients in driving smarter decisions, reducing risks, and staying ahead in a fast-evolving market environment.

About the Role:

We are seeking a trading-grade Python engineer to design and build a production-level Python platform supporting principal trading, pricing, position management, P&L, and risk workflows within a global markets environment.

The role focuses on developing a robust Python container/framework that enables quantitative teams to implement trading, pricing, and risk logic in Python while integrating seamlessly with a Quartz-style enterprise trading platform and internal data services.

Unlike analytics-focused Python roles, this position requires engineers capable of delivering mission-critical, highly reliable trading applications with the same operational standards as front-office trading and risk platforms.

The platform will support principal trading use cases that are not latency-sensitive but demand strong robustness, scalability, auditability, and production-grade engineering discipline across trade, position, valuation, and risk data flows.

Engineers will collaborate closely with quants, trading technology, risk, and platform teams across our banking client.

Key Responsibilities:

• Design and build a Python-based trading container/framework enabling quants to implement trading, pricing, and risk logic within a Quartz-style platform (e.g., Quartz, Athena, SecDB, RICE, Xing Xip, Acqa).
• Develop production-grade Python services with full trading-application reliability, controls, and SLA standards.
• Integrate Python platform components with internal market data, trade capture, position management, pricing, P&L, and risk services.
• Build APIs, service layers, and runtime infrastructure supporting principal trading and cross-asset risk workflows.
• Ensure robustness, resiliency, auditability, operational controls, and observability of trading applications.
• Contribute to Quartz-style platform architecture, deployment patterns, runtime environment design, and reusable developer tooling.
• Collaborate with quant, trading, risk, and platform teams to translate strategy and workflow needs into engineered systems.
• Support deployment and lifecycle management within enterprise trading and risk environments.
• Optimize platform usability for quant developers while maintaining production standards and front-office control requirements.

Required Skills and Experience:

• 5+ years of professional Python software engineering experience.
• Proven experience building production systems in Python, not analytics-only scripts, notebooks, or research prototypes.
• Hands-on knowledge of Quartz or comparable Python-based trading/risk platforms, including how quant logic, pricing, risk, and trade data components interact.
• Experience developing distributed or service-based systems, including microservices, APIs, containers, and internal developer frameworks.
• Experience integrating applications with market data, trade/position data, pricing, P&L, risk, or other enterprise trading services.
• Familiarity with Linux-based production environments and operational support requirements.
• Experience delivering reliable systems with uptime, SLA, monitoring, testing, and release-management expectations.
• Strong collaboration with quant, trading, risk, research, or front-office technology users in technical environments.

Preferred Qualifications:

• Experience in…