**Software Engineer III - Cloud Data Platform (AWS/Databricks, Terraform)** designs, maintains, and operates modern cloud data infrastructure on AWS using Terraform. Key responsibilities include: designing secure, scalable platform, managing Databricks, building automation around provisioning and operations, implementing CI/CD pipelines, and improving platform reliability. Proficient in AWS services, Terraform, Python/Java, and experienced in cloud infrastructure, distributed systems, and data pipelines. Collaborate cross-functionally to translate requirements into scalable platform designs. Preferred: data lakehouse architectures, AWS-native data services, data governance practices, and AWS certifications.
Full Job Description
Location: GLASGOW, LANARKSHIRE, United Kingdom
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 practicesDevelop and manage Databricks platform capabilities including workspaces, clusters, policies, jobs, libraries, and integrations to support production-grade data workloadsBuild automation around platform provisioning and operations using Python or Java, reducing manual effort and improving consistency across environmentsCreate and maintain CI/CD pipelines for infrastructure and platform deployments, including Terraform plan/apply workflows, policy checks, and automated testingImplement security best practices across the platform, including least-privilege access controls, secrets management, encryption, network segmentation, and auditabilityImprove platform reliability through observability tooling logging, metrics, and tracing alongside alerting, incident response practices, and performance and cost optimizationCollaborate with stakeholders to translate business and technical requirements into scalable platform designs, and document standards, patterns, and runbooks for team-wide useLeverage 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 standardsApply 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 automationRequired qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and proficient applied experienceStrong hands-on experience provisioning AWS infrastructure with Terraform, including modules, remote state, workspace/environment management, and change management workflowsSolid experience with core AWS services relevant to cloud data platforms, such as VPC, IAM, S3, EC2/ECS/EKS, RDS, KMS, CloudWatch, and load balancingWorking experience with Databricks, including platform administration and/or building and supporting production workloadsProficiency in Python (preferred) or Java, with demonstrated ability to build automation, tooling, and platform integrationsExperience with Git-based workflows and CI/CD practices applied to infrastructure and platform deliveryStrong troubleshooting skills across cloud infrastructure, distributed systems, and data or platform pipelinesHands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputsUnderstanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectationsPreferred qualifications, capabilities, and skills
Experience with data lakehouse architectures using Delta Lake, Apache Spark, or similar open-source frameworksFamiliarity with AWS-native data services such as Glue, Lake Formation, Redshift, or AthenaExposure to data governance practices including cataloging, lineage tracking, and data access control at the platform layerAWS certification(s) in cloud architecture, data, security, or DevOps disciplinesExperience working in regulated industries where security, auditability, and compliance are core platform requirements Build the cloud data platform that powers enterprise analytics hands-on AWS, Terraform, and Databricks engineering at scale 
