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# kdb+/q Developer

- **Company:** The Salem Group
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $228,800 - $233,875
- **Contract:** Permanent contract
- **Skills:** Query Performance, Amazon Web Services, Code Review, Modular Design, Software Engineering, Load Balancing, Stream Processing
- **Published:** October 15, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=7bbd7a0e75b7df69

## About the Role

* 5+ years of production kdb+/q experience in sell-side or buy-side trading infrastructure
 * Deep understanding of and fluency in kdb+/q - the language, the memory model, IPC, and how to make it fast at scale
 * Deep understanding of TickerPlant and knowing exactly how they work down to each line of code
 * Grounded in software development principles: testing, modular design, code review and documentation
 * Deep understanding of tick architecture: TickerPlant/RDB/HDB topology, feedhandlers, gateways, entitlements and log replay
 * Strong focus on writing clean, well-structured, maintainable q - not just code that works
 * Exposure to cloud deployment of kdb+ (AWS), * kdb+/q production: 5 years (Required)
 * deep understanding of tickerplants: 5 years (Required)
 * Tick Architecture: 5 years (Required)

## Description

* Architect, extend and harden the kdb+ tick stack: tickerplant, RDB, HDB, gateways and feedhandlers
 * Develop and optimize kdb+/q applications for real-time data processing, analysis, and storage.
 * Lead the migration from OneTick to kdb+ - data model, historical backfill, feed cutover, user migration and decommissioning
 * Maintain and occasionally extend feedhandlers for market data vendors (e.g. Bloomberg B-PIPE, MarketAxess CP+, IHS Markit, LSEG) and internal fair-value feeds - a smaller part of the role, but it's yours
 * Own the fair value / pricing data pipeline and the analytics that sit on top of it
 * Design and operate a multi-terabyte HDB at ~100 GB/day: partitioning, sym management, compression, load balancing and query performance
 * Work directly with traders and quants across the ETF desk and other groups on requirements, prototyping and production analytics; turn desk questions into robust, reusable q