Senior Software Engineer - Distributed Systems, Fanatics Markets

Fanatics Betting & Gaming•New York, NY

4h•$152,000 - $200,000•Remote

About The Position

Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect, and Bet. Fanatics Betting and Gaming is the online and retail sports betting subsidiary of Fanatics, a global digital sports platform. Fanatics Markets is the real-money prediction and trading app where you can invest in moments you care about. Built on a secure platform, we let users predict real-world outcomes and trade on events they actually follow - from sports and entertainment to political elections and beyond. Our mission is to redefine how fans engage with the moments and markets that matter most. We're looking for the right people to help us build the future of prediction markets. As a Sr Software Engineer on our Distributed Systems team, you'll be at the core of what makes Fanatics Markets work — the event-driven infrastructure that powers real-money trading at scale. This is a role for an engineer who moves fluidly between hands-on coding and architectural influence: someone who can design a system that handles massive traffic spikes during live events, then roll up their sleeves and build it. You'll work alongside some of the most experienced distributed systems engineers in the industry, owning meaningful technical decisions and directly shaping how the platform scales over the next several years. If you thrive at the intersection of high-throughput systems, low-latency design, and technical leadership — this is your seat.

Requirements

5+ years of software engineering experience with a primary focus on distributed systems and high-concurrency production environments.
Expert-level proficiency in Java or Kotlin and Spring Boot, with a strong command of modern API design — REST, gRPC, and Protobuf.
Deep hands-on experience with Kafka (or Redpanda/Pub Sub) — including internal mechanics, partition strategies, consumer group rebalancing, and delivery guarantees.
Proven ability to diagnose and resolve bottlenecks in asynchronous messaging systems and implement patterns like idempotency, distributed caching, and exactly-once processing.
Hands-on experience with Kubernetes, Helm, Terraform, and cloud-native infrastructure on AWS.
Strong instincts for production reliability — you've been on-call, triaged distributed system failures under pressure, and shipped durable fixes.
Demonstrated ability to influence technical direction across teams and guide engineers through complex architectural decisions without direct authority.
Track record of defining success metrics upfront — SLAs, latency budgets, throughput targets — and holding systems accountable to them in production.

Nice To Haves

Experience with real-time delivery systems — WebSocket fan-out, server-sent events, or pub/sub at scale.
Familiarity with financial platforms, real-time trading systems, or prediction markets.
Experience in a high-growth startup environment where ownership is broad and the technical landscape evolves quickly.

Responsibilities

Design, build, and scale distributed systems using Kotlin, Java, and Spring Boot, architecting for the traffic spikes and concurrency demands of a live real-money trading platform.
Own the development and optimization of high-throughput event pipelines using Kafka, including partition strategy, consumer group design, and exactly-once processing guarantees.
Build and tune low-latency data layers across Postgres, Redis, and Redis PubSub — ensuring data integrity, cache coherence, and sub-millisecond read paths under peak load.
Implement and enforce resilience patterns across services — backpressure handling, circuit breaking, idempotent retry logic, and graceful degradation under failure conditions.
Contribute to real-time user-facing systems, solving the fan-out problem for live market updates across tens of thousands of concurrent sessions.
Partner with product and engineering leadership to align technical execution with business priorities — contributing to build vs. buy decisions and long-term platform strategy.
Set and uphold engineering standards for observability, schema evolution, testing practices, and deployment patterns across the team — through code reviews, RFCs, and technical documentation.
Mentor and actively develop junior and mid-level engineers, raising the technical floor of the team through pairing, design reviews, and direct feedback.