Senior Backend Software Engineer

Swish Analytics
  • San Francisco, California
    6 days ago

    Job Description

    Senior Backend Software Engineer

    Company Description

    Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.

    About the Team

    The Software Engineering team builds and operates the backend systems that deliver Swish’s data products to clients. The team’s work spans high-traffic APIs and microservices, data stream processing with Kafka, developer tooling such as SDKs and CLIs, database optimization, observability, and improvements to Kubernetes workloads and cloud costs. We partner closely with infrastructure, data engineering, data science, and product teams to keep these services reliable as demand grows. We’re looking for a hands-on Senior engineer who can independently take technical ownership of core backend products, drive work across team boundaries, and help the team make sound architecture and engineering decisions.

    Responsibilities

    • 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

    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

    Preferred

    • Production experience with Kafka or comparable stream-processing systems

    • Production experience with Docker and Kubernetes

    • Experience building and operating systems at global scale, including low-latency distributed data systems

    • Experience developing, deploying, and maintaining business-critical applications

    • Experience with observability platforms and CI/CD tooling

    • Interest or experience in Go

    • Familiarity with sports data

    Base Salary: Starting at $150,000 to DOE

    Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks.

    Numbers & Facts

    LocationSan Francisco, California

    Skills

    • Application Programming Interface (API)unmatched
    • Architectural Designunmatched
    • Audio Engineeringunmatched
    • Automationunmatched
    • Building Systemsunmatched
    • Cloud Computingunmatched
    • Code Reviewsunmatched
    • Coding Standardsunmatched
    • Communication Skillsunmatched
    • Computer Engineeringunmatched
    • Computer Scienceunmatched
    • Continuous Deployment/Deliveryunmatched
    • Continuous Integrationunmatched
    • Customer Relationsunmatched
    • Data Scienceunmatched
    • Database Optimizationunmatched
    • Distributed Computingunmatched
    • Dockerunmatched
    • Documentationunmatched
    • Engineeringunmatched
    • High Availabilityunmatched
    • Machine Toolunmatched
    • Mathematicsunmatched
    • Microservicesunmatched
    • Node.jsunmatched
    • Operating Systemsunmatched
    • Predictive Modelingunmatched
    • Product Supportunmatched
    • Production Supportunmatched
    • Programming Toolsunmatched
    • Python Programming/Scripting Languageunmatched
    • Quality Assurance Methodologyunmatched
    • Relational Databases (RDBMS)unmatched
    • Reliability Engineeringunmatched
    • Software Engineeringunmatched
    • Sportsunmatched
    • Startupunmatched
    • System Operationsunmatched
    • Team Playerunmatched
    • Technical Leadershipunmatched
    • Trade-Off Analysisunmatched

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