/ TEAMS · Specialist engineering · kdb+ / q
Source engineers experienced in High-frequency time-series and capital markets data. for business-critical production systems, safe integrations and measurable technical ownership.
2,000+ engineers in our active talent network · Regional recruiters
/ SYSTEM STACK
q vector programming
kdb+ tickerplant
time-series schema
RDB HDB architecture
splayed tables
/ AVAILABLE TO HIRE
Profiles show the experience we can source. Individual candidate availability is confirmed after enquiry.
Senior kdb+ / q Engineer
Inquire availability14+ years of experience · Poland
kdb+ / q Engineer with 14 years in production systems, focused on q vector programming and kdb+ tickerplant.
Languages: Polish, English B2+
Mid-level kdb+ / q Engineer
Available3+ years of experience · Czechia
kdb+ / q Engineer with 3 years in production systems, focused on kdb+ tickerplant and time-series schema.
Languages: Czech, English B2+
Mid+ kdb+ / q Engineer
Available5+ years of experience · Serbia
kdb+ / q Engineer with 5 years in production systems, focused on time-series schema and RDB HDB architecture.
Languages: Serbian, English B2+
Senior kdb+ / q Engineer
Available7+ years of experience · Romania
kdb+ / q Engineer with 7 years in production systems, focused on RDB HDB architecture and splayed tables.
Languages: Romanian, English B2+
/ Engineering teams
Onectus uses its active engineering network and regional recruiting partners to search against concrete systems, environments and responsibilities. We evaluate practical experience rather than treating a framework mention or certification as proof of delivery. Particular availability and engagement terms are confirmed after an enquiry. For this role, practical knowledge of q vector programming, kdb+ tickerplant, time-series schema helps define the engineering search.
/ Technical specializations
The right profile depends on your actual architecture, performance constraints, integration boundaries and operational responsibilities.
kdb+ / q responsibilities include q vector programming, related kdb+ tickerplant, clear test coverage and a reliable production handover. Examine the actual tooling and deployment environment.
kdb+ / q responsibilities include kdb+ tickerplant, related time-series schema, clear test coverage and a reliable production handover. Examine the actual tooling and deployment environment.
kdb+ / q responsibilities include time-series schema, related rdb hdb architecture, clear test coverage and a reliable production handover. Examine the actual tooling and deployment environment.
kdb+ / q responsibilities include rdb hdb architecture, related splayed tables, clear test coverage and a reliable production handover. Examine the actual tooling and deployment environment.
kdb+ / q responsibilities include splayed tables, related low-latency query tuning, clear test coverage and a reliable production handover. Examine the actual tooling and deployment environment.
kdb+ / q responsibilities include low-latency query tuning, related q vector programming, clear test coverage and a reliable production handover. Examine the actual tooling and deployment environment.
/ Project scenarios
Optimize intraday market-data queries. Define constraints around q vector programming, map dependencies and test how the proposed implementation behaves under real operating conditions.
Build reliable tickerplant capture. Define constraints around kdb+ tickerplant, map dependencies and test how the proposed implementation behaves under real operating conditions.
Refactor a time-series data model. Define constraints around time-series schema, map dependencies and test how the proposed implementation behaves under real operating conditions.
Restore historical data consistency. Define constraints around rdb hdb architecture, map dependencies and test how the proposed implementation behaves under real operating conditions.
/ Practical evaluation
A senior engineering interview should surface directly relevant implementation details, debugging history and operational judgment.
Describe a production issue involving q vector programming and what evidence led to a fix.
Which decisions around kdb+ tickerplant and time-series schema were you personally accountable for?
Describe a production issue involving time-series schema and what evidence led to a fix.
Which decisions around RDB HDB architecture and splayed tables were you personally accountable for?
/ Sourcing process
Define platform versions, deployment constraints, traffic patterns, required integrations and ownership.
Search the active network and partner channels for platform-specific engineering experience.
Discuss real systems, code or configuration decisions, troubleshooting and change control.
Confirm role boundaries, location or remote access, availability, security and interviews.
Profiles, availability and engagement terms are confirmed for each request.
/ Questions
Yes. Tell us the relevant versions, operational environment and the responsibilities connected to q vector programming. We qualify hands-on experience during each search.
These can be included when central to the project. We distinguish practical implementation work from general familiarity and ask about failure scenarios and testing.
We look at production decisions, trade-offs, incident diagnosis, code or infrastructure ownership and the ability to explain decisions without relying on a technology checklist.
Share your architecture, technical constraints, collaboration model and priorities. We can then discuss relevant sourcing channels, evaluation criteria and next steps.
/ Onectus · TEAMS
Tell us the technology, production responsibilities, experience level and working model. We'll activate the appropriate engineering sourcing channels.
