KDB+/Q Data Engineer — Trading Data Pipelines & Analytics

UBS Group AG; Greater London; On-site; GBP 70,000 - 120,000; Full time

Job summary

UBS is seeking a data-focused engineer in London to develop and maintain KDB+/Q based data solutions and analytics. You will build data pipelines, models and reporting datasets, analyze large-scale data, and partner with business stakeholders to deliver effective solutions while driving root-cause analysis and ensuring platform stability.

The role emphasizes collaboration with engineering teams to modernize the broader data platform, handle production applications, and explore AI-driven workflow

Qualifications

• Extensive hands-on KDB+/Q development experience.
• Experience with trade data in an Investment Banking environment.
• Strong analytical and problem-solving skills for complex data challenges.
• Experience handling large and complex datasets.
• Good understanding of Linux environments.
• Experience supporting business-critical production applications.
• Excellent communication with both technical and business stakeholders.
• Curious about applying AI to improve workflows with sound judgment.

Responsibilities

• develop and maintain KDB+/q based data solutions and analytics
• build and enhance data pipelines, data models and reporting datasets
• analyse and process large-scale data sets
• partner with business stakeholders to understand requirements and deliver effective solutions
• investigate complex data issues and drive root-cause analysis
• support production applications and contribute to platform stability, performance and data quality
• collaborate with engineering teams to improve and modernize the broader data platform

Skills

KDB+/Q

Trade data

Analytical skills

Large datasets

Linux

Production support

Stakeholder comms

AI exploration

Job description

UBS is seeking a data-focused engineer in London to develop and maintain KDB+/Q based data solutions and analytics. You will build data pipelines, models and reporting datasets, analyze large-scale data, and partner with business stakeholders to deliver effective solutions while driving root-cause analysis and ensuring platform stability.

The role emphasizes collaboration with engineering teams to modernize the broader data platform, handle production applications, and explore AI-driven workflow