Staff Software Engineer - Streaming Data Platform

Location: New York, NY, United States; Remote

The Role

As a Staff Software Engineer on the Streaming Data Platform team in Fanatics Ecosystem, you will design, build, and operate the backend services that sit at the core of our streaming infrastructure — the systems that ingest, process, and deliver data to consumers across the company.

This is a hands-on technical leadership role. You'll write code, design systems, mentor engineers, and shape how the team builds and operates software. The right person has built streaming infrastructure before and knows what it takes to keep it running well at scale.

Responsibilities

• Design and build backend services that power our streaming data infrastructure, including ingestion, processing, and delivery to downstream systems.
• Drive large, multi-milestone projects from idea to production, ensuring they deliver outcomes that matter to the business.
• Set technical direction for the team: architecture, code quality, patterns, and tooling.
• Partner with leadership on roadmap and planning — you'll have a voice in what we build and why.
• Collaborate with platform, data, and product teams to design service boundaries, APIs, and data contracts.
• Own the test strategy for complex areas and push the team toward better testing habits and testable designs.
• Build observability, reliability, and resilience into our systems and hold the team to that standard.
• Coordinate across engineers and teams to deliver cross-cutting initiatives.
• Help diagnose and resolve performance bottlenecks related to ingestion, throughput, and distributed system behavior.
• Mentor engineers on craft, ownership, and collaboration.
• Participate in on-call rotations, drive incident resolution, and make sure retros lead to lasting fixes.
• Be open to occasional travel to Fanatics offices for meetings, events, or team gatherings.

Technical Environment

• Long-lived backend services (Go)
• Event-driven and streaming data systems (Kafka, Kafka Connect)
• Stream processing frameworks (e.g., Kafka Streams, Flink)
• Schema management and data contracts
• Observability and monitoring for streaming systems
• Infrastructure as code (Terraform)

Qualifications

• 7 +years of experience building and operating backend services at scale, with a track record of leading large technical initiatives.
• Strong experience with Go.
• Hands-on experience with Kafka or comparable streaming platforms. You've built and operated streaming infrastructure in production, including pipeline design, throughput tuning, and operational concerns like monitoring and incident response.
• Familiarity with the broader streaming ecosystem — tools like Flink, Spark, or Iceberg, and patterns around partitioning, data skew, and event-driven architectures.
• Ability to design whole systems and services with clear boundaries, well-defined APIs, and operational readiness from the start.
• Experience driving multi-milestone projects that span teams and require cross-functional coordination.
• Track record of influencing technical roadmaps and connecting engineering work to business strategy.
• History of mentoring engineers and raising the level of engineering practice around you.
• Solid understanding of distributed systems, service-oriented architectures, and system integrations at scale.
• Clear communicator who can talk about technical work with both engineers and non-engineers.
• Comfortable in a fast-moving environment where priorities shift and decisions happen quickly.
• Experience with schema management, data contracts, or data governance patterns is a plus.
• Experience building shared libraries, frameworks, or developer-facing tooling for streaming consumers is a plus.
• Experience contributing to open-source data infrastructure or streaming projects is a plus.
• Familiarity with infrastructure as code tools such as Terraform is a plus.

If you possess some of these skills but not all of them, we still encourage you to apply!

The salary range for this position is $180,500 to $237,500, which represents base pay only and does not include short-term or long-term incentive compensation. When determining base pay, as part of a final compensation package, we consider several factors such as location, experience, qualifications, and training. Remote employee may also be eligible for a home office setup stipend.

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