Job description

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 Real-Time Data & Analytics Engineering • 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 Platform Development & Architecture • 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 Data Quality, Monitoring & Controls • 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 Collaboration & Delivery • 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: • 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 Preferred Qualifications • 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 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 Primary Location Full Time Salary Range of $185,000 - $225,000.

Requirements

Must-haves

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.
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.
Real-Time Data & Analytics Engineering
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
Platform Development & Architecture
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
Data Quality, Monitoring & Controls
real-time market data
transactional and execution data
reference datasets
Build monitoring and alerting frameworks to track:
data completeness
system performance and health
Partner with production support teams to troubleshoot real-time data issues and anomalies
Collaboration & Delivery
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)

Nice-to-haves

Experience in electronic trading or algorithmic trading environments

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

apipythonjavaawsagile

Platform: oracle-cloud
Effort: medium