
11 - 50 employees
Founded 2014
đź Consulting
đŁ Marketing
đ˛ Gambling
đ° $6.9M Series B - Swish Analytics on 2019-05
Consulting ⢠Marketing ⢠Gambling
Swish Analytics is a machine-learning driven sports-odds and predictive-data company that builds a real-time odds origination engine for sportsbooks and fantasy platforms. It provides hyper-accurate player prop pricing, match and team markets, in-play and pre-game projections, and automated bet-lifecycle management to power bookmaking, bet builders, parlays, and micro-markets. Swish positions itself as a B2B provider focused on automation, accuracy, and scalable odds infrastructure for the sports betting industry.
đĽ 0 minutes ago
đ California â Remote
đľ $150k / year
â° Full Time
đ Senior
đ§âđť Full-stack Engineer
đŚ H1B Visa Sponsor
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11 - 50 employees
Founded 2014
đź Consulting
đŁ Marketing
đ˛ Gambling
đ° $6.9M Series B - Swish Analytics on 2019-05
Consulting ⢠Marketing ⢠Gambling
Swish Analytics is a machine-learning driven sports-odds and predictive-data company that builds a real-time odds origination engine for sportsbooks and fantasy platforms. It provides hyper-accurate player prop pricing, match and team markets, in-play and pre-game projections, and automated bet-lifecycle management to power bookmaking, bet builders, parlays, and micro-markets. Swish positions itself as a B2B provider focused on automation, accuracy, and scalable odds infrastructure for the sports betting industry.
⢠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
⢠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
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