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Swish Analytics

Senior Backend Software Engineer

Swish Analytics

. Serve as the technical lead and owner for core backend products, guiding work from design through implementation and production operation .

Posted 10/12/2026full-timeRemote • California • United StatesSenior💰 $150,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in backend system ownership, API design, and performance optimization, with a strong focus on high availability and reliability. Proficient in collaborating with cross-functional teams to enhance service efficiency and scalability.

Highest-signal resume keywords
Node.js Production ExperiencePython Production ExperienceHigh-Traffic API DesignKubernetes Workload OptimizationObservability Platforms Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Backend System OwnershipAPI DesignPerformance OptimizationDistributed Data SystemsRelational DatabasesNon-Relational DatabasesStream-Processing SystemsCI/CD ToolingCoding Standards ImprovementTechnical Leadership
Soft Skills
Strong Communication Skills
Tools & Technologies
DockerKubernetesKafkaObservability Platforms
Certifications & Qualifications
Bachelor's Degree in Computer ScienceBachelor's Degree in Computer EngineeringBachelor's Degree in Software Engineering
Industry Keywords
High AvailabilityScalabilityMicroservicesReal-Time Data ProcessingSports Data

Tech Stack

Tools & technologies
CloudDockerJavaScriptKafkaKubernetesMicroservicesNode.jsPythonGo

About the role

Key responsibilities & impact
  • 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

What you’ll need
  • 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