Software Engineering Lead

Description:

S&P Dow Jones Indices is seeking a highly experienced Lead Software Engineer to play a pivotal role in developing and maintaining our Fixed Income platforms. In this position, you will contribute to building scalable, reliable, and auditable solutions that support our index offerings. You will evaluate emerging technologies, lead system design efforts, and ensure the delivery of high-quality financial applications. This role involves hands-on development, team mentorship, and collaboration across cross-functional teams to drive innovation and operational excellence.

The Team

Our Fixed Income value stream focuses on delivering robust calculation engines essential for managing our fixed income indices. We operate with a product-first mindset, following Agile principles, and are committed to modernizing our technology stack to meet evolving industry standards. As a leader in this space, you will help shape the future of our index processing capabilities.

Responsibilities
 

• Design and develop high-performance calculation engines and services for fixed income indices, processing large-scale financial data efficiently.
• Collaborate with cross-functional teams to implement scalable, reliable solutions supporting critical business operations and client needs.
• Drive technical excellence through code reviews, architecture discussions, and establishing best practices for system reliability and maintainability.
• Work within Agile development cycles to deliver features that enhance our fixed income technology platform, aligning with industry standards.
• Mentor junior developers, fostering technical growth and knowledge sharing within the team.
• Lead initiatives to modernize existing systems and adopt new technologies to improve performance, scalability, and maintainability.
• Architect and oversee calculation engines and analytics services, balancing latency, throughput, cost, and accuracy.
• Implement end-to-end data lineage, reconciliation, anomaly detection, reproducibility, auditability, and version control across analytics models and data inputs/outputs.
• Lead, mentor, and grow a team of engineers and quantitative developers, setting clear expectations for technical quality and rigor.
• AI Integration: Design, develop, and deploy AI-driven solutions and machine learning models to enhance financial data processing, anomaly detection, data reconciliation, and advanced analytics.
• Independent Execution: Operate with a high degree of autonomy, quickly ramping up on complex financial domains and new technologies to drive the platform build-out with minimal oversight.