Serve as the technical lead and owner for core backend products, guiding work from design through implementation and production operation
Design and improve high-traffic, client-facing APIs and microservices, with attention to latency, availability, and correctness
Identify performance and scalability bottlenecks across applications, databases, and service dependencies, and deliver improvements supported by production measurements
Develop services that process real-time and distributed data, working with upstream teams to understand dependencies and failure modes
Create and review architecture designs, documenting important tradeoffs and explaining them to technical and nontechnical partners
Review code, provide constructive feedback, and improve coding standards, testing practices, and maintainability
Improve observability and automation so engineers can detect problems, investigate incidents, and operate services effectively
Contribute to shared tooling, Kubernetes workload optimization, and cloud efficiency in partnership with the teams responsible for those systems
Partner with infrastructure, data engineering, data science, and product teams to keep services reliable as demand grows
Requirements:
Minimum of 5 years of production software engineering experience, including demonstrated technical leadership and ownership of backend systems
Hands-on production experience with Node.js and Python
Hands-on production experience with relational and non-relational databases
Strong understanding of high-traffic APIs, distributed services, and the networking and dependencies that affect their behavior
Experience making engineering decisions that improve reliability, high availability, performance, and maintainability
Ability to independently scope ambiguous technical problems, assess tradeoffs, coordinate dependencies, and drive implementation through production rollout
Strong communication skills with technical and nontechnical stakeholders
Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or equivalent relevant experience
Production experience with Kafka or comparable stream-processing systems (preferred)
Production experience with Docker and Kubernetes (preferred)
Experience building and operating systems at global scale, including low-latency distributed data systems (preferred)
Experience developing, deploying, and maintaining business-critical applications (preferred)
Experience with observability platforms and CI/CD tooling (preferred)
Interest or experience in Go (preferred)
Familiarity with sports data (preferred)
Successful completion of background and reference checks may be required