Staff Backend Engineer

Sports Staff Backend Engineer_(Performance & Scalability)

In Sportsbook we work in a high-volume, real-time environment, integrating data feeds with our modern trading system and transactional betting platform (UI/Backend). Your contributions will cover maintaining/expanding our current Betting/Trading services acting as a hands-on technical consultant and mentor to other engineering teams, helping them solve their toughest performance and scalability challenges.

We are recruiting the best Staff Backend Engineer, Performance & Scalability for our

Sports Engineering Team!

• Act as a hands-on technical consultant and mentor to other engineering teams, helping them solve their toughest performance and scalability challenges.
• Define and drive the adoption of a scalable performance testing strategy and tooling across the organization, enabling teams to own their performance.     
• Work side by side with Principal Architects and Principal Engineers using state-of-the-art technology stack and deliver features in our microservice ecosystem
• As a Staff developer you will have a key role in owning delivery plans and aligning the product importance of reducing technical debt and prioritising platform initiatives.
• Identify obstacles to ensure quality and improve our user experience and how we build our products.
• Work with product managers, architects, QA engineers and other developers in a highly collaborative agile environment.
• Build for scale, availability, performance and security across the stack.

• 8+ years of software development experience with Java, Spring Boot and Event-Driven Architectures.
• Familiarity with Reactive Programming.
• Demonstrable, hands-on experience in performance analysis, profiling, and tuning of high-throughput, low-latency systems (e.g., garbage collection analysis, asynchronous patterns).
• Deep expertise in designing and implementing load testing strategies and familiarity with modern tooling.
• A strong understanding of observability principles and tooling for distributed systems (e.g., distributed tracing with OpenTelemetry, advanced metrics with Prometheus)
• Proven ability to design, review, and enforce non-blocking end-to-end flows in reactive systems (event-loop discipline, worker isolation, backpressure, async drivers)
• Deep understanding of event-loop vs worker execution models, including failure modes (hidden blocking, context leaks, scheduler misuse)
• Hands-on experience debugging live performance incidents in distributed systems (CPU saturation, GC storms, tail latency explosions, noisy neighbors)
• Ability to form and validate performance hypotheses under incomplete data, using production-safe techniques
• Deep JVM knowledge: allocation profiling, escape analysis, JIT behavior, safepoints, memory layout trade-offs
• Experience tuning JVMs for low-latency and high-throughput workloads (heap sizing, region sizing, pause vs throughput trade-offs)
• Ability to design realistic load models (traffic shape, burstiness, fan-out, data skew) rather than synthetic steady-state tests
• Proven track record of making pragmatic trade-offs between performance, complexity, operability, and delivery pressure
• Trusted to say no to premature optimization — and yes when it actually matters
  

• Real experience with Vert.x would be a big plus.
• Strong understanding of networking and I/O performance: TCP behavior, connection pooling, TLS overhead, backpressure across service boundaries
• Experience tuning datastores and messaging systems for throughput and latency (indexes, batching, async clients, fan-out limits)
• Designs systems where observability is part of the API contract, not an afterthought (semantic metrics, meaningful spans, cardinality discipline)
• Ability to derive actionable signals from metrics, traces, and logs under high load (not just collect them)
• Online gaming and gambling experience