MrQ is a UK-based casino operator founded in 2018, now scaling rapidly with 40 open roles (31 posted in the last 30 days). The tech stack reveals an engineering-first org: Kafka + Redis + Kubernetes form the backbone of a distributed event-streaming architecture, while heavy investment in test automation (Playwright, Cypress, k6, BrowserStack, Sauce Labs) and CI/CD (Jenkins, TeamCity, GitHub Actions) signals maturity in platform reliability. Active projects around data governance, semantic modeling, and a self-serve analytics platform indicate a shift toward data-driven player insights—matching their top pain point of self-serve analytics and the recent adoption of dbt.
MrQ operates a real-money gaming platform targeting adult players across Europe, headquartered in St Albans. Founded in 2018, the company has grown to 51–200 employees and is organized around engineering, marketing, data, and design, with particular depth in backend systems and player retention. The platform is built on a modern distributed architecture—Java/Spring services, event streaming via Kafka, caching with Redis, container orchestration via Kubernetes—and runs player-facing games alongside internal back-office tooling. Revenue and retention are driven by CRM and marketing automation (Optimove, Dotdigital, Marketo, Eloqua, Responsys) layered on top of Salesforce and HubSpot. The company faces operational pressure from AML and anti-money-laundering compliance at scale, performance bottlenecks in distributed systems, and the need to improve player onboarding and lifecycle engagement.
Backend: Java, Spring, Kafka, Redis, Kubernetes, MongoDB. Frontend: Angular, JavaScript, TypeScript. Testing: Playwright, Cypress, k6, BrowserStack, Sauce Labs. CRM: Salesforce, HubSpot, Optimove, Dotdigital, Marketo. Adopting dbt for data modeling.
Scalable automated test frameworks, data governance, self-serve analytics platform, semantic model design, internal back-office platform, design system evolution, continuous delivery, and new game launches. Also managing increased AML compliance workload.
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