VP, KDB Developer (Real Time Analytics)

Jefferies Financial GroupNew York, NY
Onsite

About The Position

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.

Requirements

  • 7+ years of experience working with large-scale financial datasets, including: real-time market data, order/execution data, 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
  • Strong analytical, problem-solving, and communication skills
  • Ability to work effectively in a fast-paced, collaborative environment

Nice To Haves

  • Experience in electronic trading or algorithmic trading environments
  • Familiarity with: market microstructure and trading workflows, low-latency system design principles
  • 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

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 (tickerplant, 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
  • Develop and automate data quality checks across: real-time market data, transactional and execution data, reference datasets
  • Build monitoring and alerting frameworks to track: latency, data completeness, 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

Benefits

  • Full Time
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