Software Engineer III - Cloud Data Platform Engineering (AWS , Terraform & Databricks)

Your expertise in cloud infrastructure and data platforms can shape how an entire enterprise accesses, processes, and trusts its data. At JPMorganChase, we build platforms that operate at a scale few organizations ever encounter — and we do it with a team that values craftsmanship, collaboration, and continuous improvement. This is an opportunity to grow your skills, deepen your cloud and data platform expertise, and make a direct impact on solutions that matter to the business and the people it serves.

As a Software Engineer III at JPMorganChase within the Cloud Data Platform team, you will be hands-on designing, provisioning, and operating a modern cloud data platform built on AWS and Databricks. You will partner with data engineers, security, and platform teams to deliver infrastructure that is scalable, secure, and production-ready. Your work will enable reliable, well-governed analytics workloads that drive insight and decision-making across the firm.

Job responsibilities

• Design, build, and maintain cloud infrastructure on AWS using Terraform, including networking, security, compute, storage, and managed services, following infrastructure-as-code best practices

• Develop and manage Databricks platform capabilities — including workspaces, clusters, policies, jobs, libraries, and integrations — to support production-grade data workloads

• Build automation around platform provisioning and operations using Python or Java, reducing manual effort and improving consistency across environments

• Create and maintain CI/CD pipelines for infrastructure and platform deployments, including Terraform plan/apply workflows, policy checks, and automated testing

• Implement security best practices across the platform, including least-privilege access controls, secrets management, encryption, network segmentation, and auditability

• Improve platform reliability through observability tooling — logging, metrics, and tracing — alongside alerting, incident response practices, and performance and cost optimization

• Collaborate with stakeholders to translate business and technical requirements into scalable platform designs, and document standards, patterns, and runbooks for team-wide use

• Leverage enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards

• Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation

Required qualifications, capabilities, and skills