SVP Senior KDB+ Platform Engineer

Citi’s Equities Technology organization is seeking a hands‑on Senior Software Engineer to join the Equities Timeseries group, a strategic, horizontal platform organization responsible for order data, tick data, and real‑time and historical Transaction Cost Analytics (TCA) supporting global Equities trading.

Within this broader Timeseries organization, the role will focus on strategic time‑series data platforms that provide the analytics, canonical data models, and performance‑critical infrastructure underpinning electronic execution globally, including Algorithmic Trading and Smart Order Routing (SOR).

The successful candidate will play a senior technical leadership role in the design, implementation, and evolution of these platforms, contributing to architecture decisions under microsecond-level latency constraints, defining and governing time‑series data models, and ensuring the correctness, explainability, and performance of analytics used across Citi’s electronic execution ecosystem.

This role requires close, continuous collaboration with trading desks, product partners, and quantitative research teams globally, with strong alignment to firm‑wide strategy and cross‑regional delivery.

Responsibilities

• Design and develop next‑generation time‑series analytics platforms supporting multiple execution‑critical systems within the Equities Timeseries organization.
• Own and evolve high‑performance KDB+/q (or equivalent) platforms used for order, execution, market data, and TCA analytics, across both real‑time and historical use cases.
• Define, govern, and maintain canonical time‑series schemas and data models that are shared across Algorithmic Trading, SOR, and other electronic execution consumers.
• Contribute to architectural decisions for ultra‑low‑latency, high‑throughput systems, ensuring analytics can operate under microsecond‑level constraints.
• Partner closely with traders and quantitative researchers to co‑design and productionize analytics, translating research ideas into reliable, production‑grade time‑series systems.
• Drive high standards in code quality, automated testing, and SDLC discipline, with a focus on analytics correctness and repeatability.
• Continuously improve testing frameworks, development tools, and environments to support platform reliability at scale.
• Leverage Citi’s AI‑powered SDLC tooling to enhance developer productivity, code quality, and innovation.
• Build and maintain shared platform capabilities for monitoring, reconciliation, traceability, recovery, and auditability of electronic trading analytics.

Qualifications

• Proven hands‑on engineering experience with deep technical expertise in low‑latency time series databases, using KDB+/q. Experience in Java, C++ will be desired.
• Deep expertise in KDB+/q or equivalent high‑performance time‑series platforms, with demonstrated ownership of production systems.
• Prior experience building or owning Algorithmic Trading, SOR, Market Making, or Quantitative Trading time series platforms at a global financial institution.
• Strong understanding of market microstructure, electronic execution workflows, and regional exchange and regulatory regimes.
• Proven ability to design and operate systems where analytics correctness is non‑negotiable, even under extreme performance constraints.
• Strong understanding of performance optimization, and high‑throughput architectures.
• Experience defining and governing shared data models used by multiple downstream systems.
• Ability to prioritize multiple initiatives and deliver in a fast‑paced, globally distributed environment.
• Excellent communication skills, with the ability to reason and explain complex systems to engineers, quants, and trading stakeholders.

Education

• Bachelor's degree / University degree in Computer Science, Engineering, or a related field, or equivalent professional experience.

Job Family Group: Technology

Job Family: Applications Development

Time Type: Full time

Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

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