You will join Guidewire’s Product organization, working at the intersection of data, AI, and cloud infrastructure to power our industry-leading P&C insurance platform. Our team focuses on building secure, scalable, and governed data capabilities that enable AI-infused products and analytics for customers worldwide. We collaborate across Product Development, Security, and Finance to ensure our data platform is robust, reliable, and ready for rapid innovation. In this role, you will design and automate modern data infrastructure on AWS to support Guidewire’s AI-first Product strategy, including Agentic AI Platform initiatives and next-generation analytics experiences. You will lead Data. Ops practices—CI/ CD, observability, and governance—for critical pipelines and data products that power our Claims, Underwriting, and pricing solutions globally. If you are excited by Gen. AI, large-scale data systems, and building the backbone that helps insurers operate more efficiently, this role puts you at the center of Guidewire’s mission to transform how the world’s P&C insurers do business. Job Description. What you’ll do. Architect, automate, and maintain production-grade data infrastructure on AWS (e.g., S 3, EMR, Glue, Lambda, Redshift) using Terraform or CDK, with a focus on high availability, security, and consistent environments across the SDLC. Integrate Claude Code and other LLM-based agents into the engineering workflow to accelerate infrastructure provisioning, refactoring, and generation of technical documentation, embedding AI into daily development practices. Design, build, and optimize CI/ CD pipelines that test, deploy, and monitor dbt models and AWS Glue/ Spark jobs, ensuring reliable, repeatable delivery of governed data assets. Implement agentic operations for Data. Ops—configuring AI agents to triage and perform root-cause analysis of pipeline failures, surface cost-optimization signals, and proactively detect schema drift or data quality regressions. Engineer scalable, well-governed data pipelines and tables using Apache Iceberg, Airflow (MWAA), and Redshift, emphasizing simplicity, reusability, and clear ownership of data products. Operationalize security and compliance best practices in a regulated insurance environment, including IAM automation, encryption, audit-ready logging, and alignment with enterprise RBAC/ MFA standards. Partner with Product Strategy, PDO, and data science teams to ensure data platforms and features can support AI-heavy products like the Agentic AI Platform, Claim Summary, and Underwriting Assistant at scale. At Guidewire, we foster a culture of curiosity, innovation, and responsible use of AI—empowering our teams to continuously leverage emerging technologies and data-driven insights to enhance productivity and outcomes. What you’ll bring. Required. Demonstrated ability to embrace AI and apply it to your current role as well as data-driven insights to drive innovation, productivity, and continuous improvement . years of experience in Data Engineering, Data Operations, or Platform Engineering building and operating cloud data infrastructure. Deep proficiency with AWS (e.g., S 3, EMR, Glue, Lambda, Redshift) and infrastructure-as-code (Terraform strongly preferred; CDK a plus), including designing secure, resilient architectures. Strong experience with dbt in production (modeling, testing, documentation, deployment) and modern table formats such as Apache Iceberg for large-scale analytics. Advanced SQL skills (performance tuning, complex joins and window functions) and solid Python experience for automation, orchestration, and data engineering tasks. Hands-on experience with Apache Spark for large-scale batch or streaming workloads, ideally on AWS EMR or Glue. Proven track record of building or maintaining CI/ CD pipelines (Git-based workflows, automated testing, deployment, and monitoring) for data and analytics workloads. Strong systems thinking and data modeling skills (e.g., Kimball, Data Vault) and familiarity with integrating RDBMS data via CDC patterns. Clear, collaborative communication style with the ability to work across product, security, and business stakeholders in a distributed environment. Preferred. Experience leveraging Claude Code, LLM-based agents, or other agentic AI tools to automate infrastructure provisioning, refactoring, or documentation workflows. Background working with ML - Ops platforms such as Sage. Maker, especially around feature stores and data contracts between data engineering and ML teams. Experience in a regulated environment (Finance, Insurance, or similar) and familiarity with P&C insurance data concepts (policies, claims, billing, rating, underwriting). Exposure to Redshift performance tuning, workload management, and cost optimization in enterprise settings. Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. Your Impact. We believe in clarity and setting you up for success. In your first six months, you will take ownership of key AWS-based data environments, stabilize and enhance existing dbt/ Glue/ Spark pipelines, and introduce AI-augmented workflows that reduce operational toil and improve developer productivity. You will help Product Strategy and PDO deliver reliable, trusted data for AI-powered products like the Agentic AI Platform and Claim Summary, while aligning with security and governance priorities for a global P&C customer base. Over time, your work will shape how Guidewire’s customers access, trust, and use data—directly influencing product quality, operational excellence, and our mission to transform how insurers serve their policyholders worldwide. What’s in it for you. The people we employ give their all, and in return, we offer flexibility wherever we can, such as:Flexible work environment. Health and Wellness benefits. Paid time off programs including volunteer time off. Market-competitive pay and incentive programs. Continual development and internal career growth opportunities. All new hires participate in our in-person orientation, where you’ll connect with colleagues, learn about