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Kdb​/Q Engineer – Data & Analytics; Equities

Job in New York, New York County, New York, 10261, USA
Listing for: Jefferies
Full Time position
Listed on 2026-07-19
Job specializations:
  • Software Development
    Data Engineering, SQL Developer
Salary/Wage Range or Industry Benchmark: 180000 - 260000 USD Yearly USD 180000.00 260000.00 YEAR
Job Description & How to Apply Below
Position: Kdb+/Q Engineer – Real-Time Data & Analytics (Equities)
Location: New York

Location: New York, NY

Overview

The Equities Data & Analytics Team is seeking an experienced Kdb+/Q Engineer to design, build, and enhance real-time analytics platforms supporting electronic trading and market data workflows.

This role focuses on developing and maintaining low-latency data infrastructure
, processing real-time ticker data alongside large-scale historical datasets
, and delivering high-performance analytics solutions used by trading, quantitative, and risk teams.

The successful candidate will operate in a fast‑paced environment, partnering closely with traders, quants, developers, QA, and production support teams to create scalable, reliable, and secure data systems.

Key Responsibilities
  • Design and develop low-latency kdb+/q systems to ingest, process, and analyze real-time market data, ticker data, and order/execution flows
  • Build and optimize streaming analytics pipelines to support intraday monitoring and analytics use cases
  • Develop efficient time-series data models and query frameworks for both real-time and historical datasets
  • Enhance system performance for high-throughput, low-latency analytics workloads
  • Architect and implement scalable kdb infrastructure (ticker plant, RDB, HDB) supporting enterprise data needs
  • Develop and maintain API‑driven data services for downstream consumers, including trading and analytics applications
  • Build reusable, library‑grade components to standardize data access, transformation, and analytics functionality
  • Implement secure access controls and authentication layers for data platform usage
Data Quality, Monitoring & Controls
  • Develop and automate data quality checks across:
  • transactional and execution data
  • Build monitoring and alerting frameworks to track:
  • system performance and health
  • Partner with production support teams to troubleshoot real‑time data issues and anomalies
  • Collaborate with traders, quants, and engineering teams to translate business requirements into scalable technical solutions
  • Contribute across the full software development lifecycle (design, development, testing, deployment, and optimization)
  • Produce clear and comprehensive technical documentation and system designs
  • Ensure adherence to best coding practices and industry standards
Required Qualifications
  • 7+ years of experience working with large-scale financial datasets, including:
  • positions or time-series data
  • 7+ years of hands‑on Kdb+/Q experience
    , including real-time data systems
  • Strong experience working in Linux/Unix environments
  • Solid understanding of:
  • time-series databases and architectures
  • real-time data streaming and processing
  • analytical, problem‑solving, and communication skills
  • Ability to work effectively in a fast‑paced, collaborative environment
Preferred Qualifications
  • Experience in electronic trading or algorithmic trading environments
  • Familiarity with:
  • market microstructure and trading workflows
  • Working knowledge of Python or Java for integration and tooling
  • Experience implementing authentication and entitlement frameworks
  • Exposure to cloud platforms (e.g., AWS)
  • Experience with Agile development methodologies
Key Attributes
  • Strong ownership mindset and ability to deliver end‑to‑end solutions
  • Ability to think critically and propose innovative ideas

    Proven track record of delivering high‑quality systems in production environments
  • Collaborative team player with strong communication skills
What This Role Offers
  • Opportunity to work on mission‑critical, real‑time analytics systems
  • Direct exposure to front‑office trading environments and workflows
  • Ownership of high‑impact data infrastructure and platforms
  • A combination of kdb engineering, real‑time systems, and advanced analytics development
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