Senior Software Engineer

FactSet creates flexible, open data and software solutions for over 200,000 investment professionals worldwide, providing instant access to financial data and analytics that investors use to make crucial decisions.  

At FactSet, our values are the foundation of everything we do. They express how we act and operate, serve as a compass in our decision-making, and play a big role in how we treat each other, our clients, and our communities. We believe that the best ideas can come from anyone, anywhere, at any time, and that curiosity is the key to anticipating our clients’ needs and exceeding their expectations.  

Python & C++ Senior Software Engineer – Data Access (FIP)

FactSet is seeking a highly skilled Senior Software Engineer to join our Data Access team — the single, powerful entry point to the FactSet Intelligence Platform (FIP). This is where every interaction begins: AI agents & tools, internal analytics, and client-facing APIs all connect through one unified endpoint and receive responses in a consistent, structured envelope enriched with provenance, source attribution, and entitlement transparency. Operating at the very front of FactSet's data ecosystem, you'll define this client-facing interface and orchestrate the systems behind it, delivering data with exceptional speed, security, reliability, and precision.

The platform handles immense volumes of low-latency requests, so strong engineering discipline is essential — you'll apply best practices in distributed systems, scalability, and performance to build infrastructure that is both resilient and efficient. It's a unique opportunity to shape a critical layer of FactSet's architecture, one that directly shapes the client’s experience and enables the next generation of intelligent applications. If you're passionate about building high-performance systems, simplifying complex data interactions, and making a measurable impact at scale, we'd love to hear from you.

Responsibilities

• Design, develop, and deploy the Data Access interface that defines how clients access data.
• Implement query patterns and APIs that balance flexibility, performance, and security.
• Enforce entitlements to ensure clients access only authorized data products.
• Leverage metrics and KPIs to optimize query execution, incorporating caching and performance strategies to meet client SLAs.
• Build observability into the layer — end-to-end request tracing, provenance, and source attribution surfaced in responses.
• Own Data Access products and features, driving bug fixes, performance enhancements, and scalability improvements.
• Collaborate with stakeholders and cross-functional teams to continuously improve development processes.
• Mentor junior engineers and contribute to technical design reviews and architecture decisions for the Data Access layer.
• Participate in a regional on-call rotation to support production system

Required Qualifications

• Bachelor's Degree or equivalent in Computer Science or related field.
• 5+ years of software engineering experience with a focus on API development, query systems, or data infrastructure.
• Strong proficiency in Python and C++, with experience building production-grade, client-facing systems.
• Solid understanding of OOP principles and software design patterns.
• Experience with API design and building orchestration layers across multiple backend systems.
• Proven ability to work independently and collaboratively, with experience leading technical initiatives.
• Passion for designing and implementing efficient, scalable, and maintainable software.

Preferred Qualifications

• Experience with multithreaded programming, low latency, and high-availability systems.
• Knowledge of query engine architecture, parsers, compilers and interpreters.
• Experience implementing caching strategies (Redis, Memcached) for query results and metadata.
• Experience with service-oriented architecture and microservices design.
• Understanding of distributed systems and handling failures gracefully across service boundaries.
• Experience working with large-scale data systems and balancing latency, throughput, and cost.
• Background with rate limiting, throttling, and client quota management.