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

JPMorgan Chase & Co.; Greater London; On-site; GBP 90,000 - 120,000; Full time

Job summary

JPMorganChase in London seeks an experienced Software Engineer III to design, provision, and operate a modern cloud data platform on AWS and Databricks. You will partner with data engineers, security, and platform teams to deliver scalable, secure infrastructure that supports production analytics across the enterprise.

Your work will emphasize automation, governance, and reliable delivery, leveraging Terraform, Databricks, and CI/CD, while integrating enterprise‑grade AI-assisted tooling to

Qualifications

• Formal training or certification on software engineering concepts.
• Hands-on AWS infrastructure provisioning with Terraform including modules and remote state.
• Experience with core AWS services (VPC, IAM, S3, EC2/ECS/EKS, RDS, CloudWatch).
• Experience with Databricks platform administration and production workloads.
• Proficiency in Python or Java with automation and tooling experience.
• Experience with Git-based workflows and CI/CD for infrastructure and platform delivery.
• Knowledge of security, observability, and cost optimization in cloud platforms.

Responsibilities

• Design, provision, and operate cloud infrastructure on AWS using Terraform.
• Develop Databricks platform capabilities for production workloads.
• Build automation around platform provisioning using Python or Java.
• Create CI/CD pipelines for infrastructure deployments.
• Implement security best practices across the platform.
• Improve platform reliability with observability, metrics, and cost optimization.
• Collaborate with stakeholders to translate requirements into scalable designs.
• Validate AI-assisted development outputs with peer review and testing.
• Utilize SDLC tools including AI-assisted development and automation capabilities.

Skills

Cloud design

Automation

Security best practices

AI-assisted development

Education

Formal software engineering certification

Tools

AWS Terraform

Databricks

Python

Java

CI/CD pipelines

Git workflows

Job description

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

• Formal training or certification on software engineering concepts and proficient applied experience
• Strong hands‑on experience provisioning AWS infrastructure with Terraform, including modules, remote state, workspace/environment management, and change management workflows
• Solid experience with core AWS services relevant to cloud data platforms, such as VPC, IAM, S3, EC2/ECS/EKS, RDS, KMS, CloudWatch, and load balancing
• Working experience with Databricks, including platform administration and/or building and supporting production workloads
• Proficiency in Python (preferred) or Java, with demonstrated ability to build automation, tooling, and platform integrations
• Experience with Git‑based workflows and CI/CD practices applied to infrastructure and platform delivery
• Strong troubleshooting skills across cloud infrastructure, distributed systems, and data or platform pipelines
• Hands‑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 outputs
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations

Preferred qualifications, capabilities, and skills

• Experience with data lakehouse architectures using Delta Lake, Apache Spark, or similar open‑source frameworks
• Familiarity with AWS‑native data services such as Glue, Lake Formation, Redshift, or Athena
• Exposure to data governance practices including cataloging, lineage tracking, and data access control at the platform layer
• AWS certification(s) in cloud architecture, data, security, or DevOps disciplines
• Experience working in regulated industries where security, auditability, and compliance are core platform requirements