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Guidewire

Cloud-based SaaS platform for P&C insurers

Senior Site Reliability Engineer - Data Platform

Site Reliability EngineeringUpdated on Nov 12
Full-timeKuala Lumpur, Federal Territory of Kuala Lumpur, MalaysiaNo salary listedHybrid

About the Job

Requirements

  • At least 8 years of relevant industry experience in Site Reliability Engineering, DevOps, Production Engineering, or similar roles supporting large-scale distributed systems and data platforms.
  • A BS or MS in Computer Science, Computer Engineering, or Mathematics, or equivalent practical experience.
  • Strong experience continuously deploying and operating public-cloud services on AWS, including production support and on-call responsibilities.
  • Hands-on experience running cloud data platforms using big data and streaming technologies such as Kafka, Hadoop, Spark, and Hive.
  • Proficiency in at least one of Java, Go, or Python, and solid scripting skills for building tools, automation, and integrations.
  • Experience building and operating microservices, including REST APIs and/or gRPC services.
  • Experience with CI/CD tools such as TeamCity and GitHub Actions for automated builds, tests, and deployments, including promotion gates.
  • Strong experience with Infrastructure as Code tools such as Terraform and AWS CloudFormation for provisioning and managing cloud infrastructure.
  • Practical knowledge of Kubernetes, such as AWS EKS, and Docker, including deployment patterns, service discovery, and resource management.
  • Familiarity with AWS services relevant to data and distributed systems, such as RDS, EMR, Redshift, MSK, ECS, SNS, and SQS.
  • Expertise with monitoring, logging, and observability tools such as Datadog and ELK to instrument services and build actionable alerts and dashboards.
  • Deep understanding of distributed systems fundamentals, networking, storage, operating systems, and their interactions in complex multi-tier environments.
  • Knowledge of capacity planning, scalability, and resilience patterns, including blue/green and canary deployments and chaos engineering concepts.
  • Demonstrated experience solving infrastructure and application problems using software engineering approaches rather than only manual operations.
  • Familiarity with agile methodologies such as Scrum and Kanban.
  • Strong analytical and troubleshooting skills for complex, distributed, multi-service environments.
  • Experience with on-call work, incident response such as PagerDuty, and post-incident review processes, with a focus on learning and continuous improvement.
  • Ability to collaborate with engineering, data, and operations teams to understand their systems and help improve them.
  • A big-picture perspective on systems, tools, and customer value, aligning technical decisions with priorities around operational excellence, AI, cloud, and data platform adoption.
  • Comfort with agile development methodologies and iterative delivery in a collaborative environment.
  • Eagerness to learn, experiment, and grow, staying current with emerging technologies across cloud, data, and SRE practices and applying them thoughtfully.

Responsibilities

  • Design and implement self-service automation and tooling in Go, Python, or scripting languages to standardize and streamline deployment, operations, and troubleshooting for data-platform services.
  • Implement and improve CI/CD pipelines, such as TeamCity and GitHub Actions, to support safe, frequent deployments, including promotion gates and automated quality checks.
  • Use Infrastructure as Code, such as Terraform and AWS CloudFormation, to build, harden, and maintain repeatable cloud infrastructure for data and analytics workloads.
  • Operate and improve Kubernetes-based environments, including AWS EKS, by deploying, scaling, and managing the lifecycle of containerized data services such as Docker-packaged microservices and streaming jobs.
  • Apply progressive delivery strategies such as blue/green and canary deployments, and support chaos-engineering experiments to validate resilience and recovery mechanisms.
  • Collaborate on capacity planning and cost-aware design for cloud compute, storage, and networking resources used by data-intensive systems.
  • Build and refine end-to-end data-platform observability using monitoring and logging tools such as Datadog and ELK, including metrics, traces, and logs.
  • Develop dashboards and alerts that provide visibility into data-pipeline health, customer experience, and platform performance.
  • Analyze operational data to identify reliability risks and bottlenecks, and feed insights into the roadmap and reliability backlogs.
  • Partner with product engineering, data-platform, security, and other SRE teams to define and implement service-architecture and operational-practice improvements supporting PDO's AI, cloud, and data-platform priorities.
  • Advocate for reliability, resilience, and operational excellence in design reviews, readiness assessments, and release planning.
  • Contribute to an inclusive work environment based on accountability, continuous learning, and psychological safety.

Desired Qualifications

  • Familiarity with KubeVela or Crossplane.
  • Kubernetes or AWS certifications.
  • Contributions to open-source projects.

About the Company

Guidewire

Cloud-based SaaS platform for P&C insurers

Guidewire provides software for the property and casualty (P&C) insurance industry. Its platform is a cloud-based suite that helps insurers run core operations such as underwriting, policy administration, billing, and claims, with added analytics and AI features. Customers subscribe to the software as a service (SaaS) and pay for cloud access, implementation, and ongoing support. The company differentiates itself by its deep specialization in P&C, a large number of successful implementations (about 1,600), a track record of industry recognition (awards and a strong position in Gartner’s Magic Quadrant for P&C Core Platforms in North America), and an integrated set of digital, core, analytics, and AI tools designed to modernize insurers’ core systems. Its goal is to help P&C insurers modernize their technology, improve customer experiences, and grow their businesses through a cloud-based platform.

Company size
1,001-5,000
Company stage
IPO
Headquarters
San Mateo, CA
Founded
2001

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