Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

• Lead the architecture and development of KDB+/q-based systems for real-time and historical data processing.
• Design, develop, and maintain KDB+/q applications for real-time and historical data ingestion, analytics, and processing
• Build and optimize time-series databases that support trading, risk, and research systems Create data loaders, APIs, and tools to support quantitative researchers, traders, and portfolio managers
• Build or maintain HMI trading infrastructure, including simulation or back-testing platforms
• Tune system performance, troubleshoot issues, and ensure reliability and scalability
• Collaborate with stakeholders-traders, analysts, quants, and other developers-to translate business needs into technical solutions
• Participate in peer code reviews, contribute to architecture discussions, and facilitate knowledge transfer
• Support production deployments, including testing, monitoring, and system health maintenance Candidate Profile / Required Qualifications
• Proficiency in KDB+ and the q programming language-ideally with 2-5+ years of hands-on experience in a trading, quant analytics, or financial services environment
• Strong understanding of time-series data structures, real-time data processing, and tick-level data handling
• Adept at performance tuning, query optimization, and building scalable systems
• Familiarity with Python or other languages for integration or supporting tooling (commonly used alongside KDB+)
• Excellent communication skills and ability to work in cross-functional teams, including quantitative researchers and technology groups
• A degree in Computer Science, Engineering, Mathematics, or related field is often preferred
• Bonus: Experience with equities, high-frequency trading, simulation frameworks, or investment banking/hedge fund environments