S&P Global's Data Delivery Exchange Data team needs to operate a high-performance platform that processes real-time data from over 125 global exchanges 24/7, delivering over 2,500 daily price snapshots and maintaining live streaming services that power financial decisions across the globe. The team is looking for individuals to build and maintain the infrastructure that connects global financial markets to clients through cutting-edge data aggregation and enrichment services.
Requirements
- 5+ years of software development experience with distributed systems and high-performance applications
- Strong proficiency in programming languages such as Java, Python, C++, or Go
- Experience with real-time data processing frameworks and streaming technologies
- Knowledge of database technologies including both SQL and NoSQL solutions (such as PostgreSQL, Cassandra or other)
- Experience with cloud platforms and containerization technologies (such as AWS, Azure, Container platforms or other Cloud-native orchestration tools)
- Experience in financial services, capital markets, or real-time trading systems
- Knowledge of market data protocols and exchange connectivity (such as FIX, FAST, or proprietary exchange feeds)
Responsibilities
- Design and develop high-performance systems that process real-time financial data from 125+ global exchanges operating 24/7
- Build and maintain multi-replica caching systems that serve latest-value queries and streaming services to global clients
- Implement data enrichment services including primary listing identification, future rollovers, and consolidated pricing models
- Develop robust reference data capabilities with complex linking, corporate event handling, and data retention enforcement
- Generate and optimize over 2,500 daily price snapshots consumed by clients worldwide
- Collaborate with cross-functional teams to ensure system reliability and scalability for mission-critical financial data delivery
Other
- Bachelor's degree in Computer Science, Engineering, or related technical field, or equivalent practical experience
- Experience with caching technologies and in-memory data grids (such as Redis, Hazelcast, or Apache Ignite)
- Strong understanding of system performance optimization and low-latency design principles
