Senior kdb+ Architect; Greenfield Project

Every query matters. Every millisecond counts. Every system you build shapes the future of data-driven finance.

At
Data Intellect
, we thrive on solving complex data challenges in high-stakes environments. We’re a team of engineers, problem-solvers, and collaborators who believe in pushing boundaries, not egos.

If you're a seasonedkdb+ engineer ready to lead, innovate and make an impact - we want to hear from you.

We have a rare opportunity for a Senior kdb+ Architect based in New York to lead a greenfield kdb+ platform build for a top‑tier Investment Banking client. This role offers true end‑to‑end ownership, spanning real‑time and historical market data ingestion through to high‑performance analytics and downstream visualisation.

You’ll play a pivotal role in defining and shaping the overall system architecture, making critical design decisions around data models, scalability, performance and resiliency. The work sits at the heart of the market data stack and demands deep expertise in kdb+/q, low‑latency systems, market data feeds and analytic frameworks.

This is an excellent opportunity for a senior engineer who wants to influence technical direction, work closely with front‑office-aligned systems and build a strategic platform from the ground up while showcasing their architectural and performance optimisation expertise.

As a Senior kdb+ Engineer at [DI] you’ll be at the forefront of delivering high-performance, scalable solutions for some of the world’s most data-intensive financial institutions. You’ll:

• Lead technical delivery
  on client projects, setting the standard for quality and performance.
• Design and implement robust kdb+ architectures
  that handle billions of rows of time-series data.
• Collaborate with quants, traders, and analysts
  to translate business needs into performant, efficient code.
• Mentor and guide
  junior and mid-level developers, fostering a culture of technical excellence.
• Own the full development lifecycle
  by developing, testing, supporting and maintaining all code for client applications
• Drive innovation
  by staying ahead of the curve in kdb+, q, and adjacent technologies.

• 5+ years of hands-on kdb+ development, with deep expertise in q and time-series data.
• Proven experience designing and implementing kdb+ architectures and scalingkdb+ systems in production.
• Experience working with and architecting both real-time and historical systems.
• Strong background inUnix/Linux environments and scripting.
• Demonstrated technical leadership and decision-making in fast-paced projects.
• Excellent communication skills to explain complex systems to both technical and non-technical stakeholders.
• Experience incapital markets or investment banking, understanding the domain and its demands.
• A passion for clean, performant code and continuous improvement.

• Experience with Python,cloud platforms(AWS, GCP, Azure), or other time-series databases.
• Exposure totick data,real-time analytics, or electronic trading systems.
• People management or team leadership experience.

• Global opportunities
  – work with clients in London, New York, Hong Kong, Singapore, and beyond.
• Continuous learning
  – access to paid training, certifications, and leadership development.
• Clear progression paths
  – biannual promotion cycles and regular 1:1s to support your growth.
• Healthcare & wellbeing
  – provider dependent on region.
• Referral bonuses, social events, and more
  – we work hard and celebrate harder.

Data Intellect
is a specialist data and technology consultancy with deep roots in capital markets. We build high-performance systems that power trading, risk, and analytics for some of the world’s most demanding clients. Our expertise spanskdb+,data engineering,regulatory tech, and enterprise platforms and we’re growing fast.

We’re proud to be an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Accommodations are available throughout the assessment and selection process.