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Our Teams

Engineering

Engineering

As an engineer at a global financial technology company, you’ll be an integral part of FactSet's success. Our Engineering team is composed of highly talented and motivated individuals who value using cutting-edge technology to present creative solutions. Our engineers find the right balance between FactSet's flexible environment where everyone can contribute individually, yet at the same time cultivate a community where they can depend on each other for help, learning, and development.

Software Engineers

FactSet Software Engineers are creative, talented professionals. They work closely with other departments to ensure FactSet's products and technologies are responsive to the changing needs of the investment community. Software Engineers design and implement applications using various technologies for integration within the FactSet product suite and deployment to investment professionals worldwide. A Software Engineer is typically responsible for all phases of development and works closely with product managers and the sales team.

Systems Engineers

Systems Engineers are responsible for research, design, implementation, and support of multiple technologies in a high availability production environment. These groups interact with clients, internal departments, and external vendors to evaluate, test, and deploy technology solutions. Systems Engineers are dedicated to quality operational support and proactively monitor system performance, health, and capacity trends while responding immediately to any faults. These engineers have flexible scheduling and share on-call responsibilities, as system upgrades and maintenance are frequently performed outside of normal business hours. Systems Engineering includes Network, Server, Desktop, and Security teams.

Natural Language Processing Engineers

This role works to develop and maintain the internal data system that supports FactSet client needs. The primary responsibility for this position is the development and maintenance of systems for processing financial data, with a focus on natural language text analysis.