Data Engineer

Mindbox connects top IT talents with technology projects for leading enterprises across Europe. This position is for an experienced Data Engineer who can design robust solutions, optimise performance, and contribute to high-availability, globally distributed infrastructures. Training on kdb+/q will be provided, requiring prior experience with large-scale, real-time data systems.

• Experience handling large-scale datasets and distributed systems in production environments
• Proven ability to optimise low-latency, high-volume queries and processes
• Strong scripting and software engineering skills in Python and Bash; Git for version control
• Practical knowledge of Unix/Linux environments, CI/CD automation, and deployment strategies
• Experience in at least one capital markets domain (FX, Rates, Equities, Credit or Commodities)
• Understanding of electronic trading, market risk, and pricing systems
• Familiarity with test automation, pipelines, and secure coding principles
• Strong troubleshooting and performance profiling capabilities
• Ability to work under high availability and resiliency standards

Nice to have:

• Prior exposure to kdb+/q or functional programming paradigms
• Background in analytics platforms, AI/ML integration, anomaly detection, or time-series data
• Previous experience in a global investment bank or electronic trading firm

• Develop and optimise kdb+ queries and services for ultra-low latency, high-throughput data solutions
• Build aggregation layers and pipelines consumed by APIs, AI/ML models, and dashboards
• Expose time-series and analytics data through API gateways and integration layers
• Collaborate with data science and AI teams to provide structured, high-quality datasets for predictive models
• Implement advanced monitoring, alerting, and performance tuning for production systems
• Ensure redundancy, failover, and disaster recovery strategies meet operational risk criteria
• Partner with traders, quants, and product owners to translate analytical requirements into efficient data solutions
• Adhere to data governance, compliance, and secure coding standards
• Contribute to code reviews, CI/CD best practices, and engineering process improvements