Engineer

Jumping Rivers Ltd; Newcastle upon Tyne; On-site; GBP 50,000 - 75,000; Full time

Job summary

Jumping Rivers Ltd is seeking an Engineer to deploy, configure, and maintain data science software for clients across cloud and on-premise environments. You will blend hands-on infrastructure delivery with ongoing technical support to keep systems stable, secure, and performant.

You will work closely with clients and the wider Engineering team to deliver reliable deployments, monitor health, and assist with security and compliance.

Qualifications

• Experience in a DevOps, infrastructure, or systems engineering role.
• Hands-on with at least one major cloud provider (AWS/Azure/GCP).
• Experience with Infrastructure-as-Code (Terraform, Ansible, or similar).
• Comfortable working in Linux environments.
• Understanding of networking fundamentals (DNS, load balancing, VPNs, firewalls).
• Strong, methodical troubleshooting skills.

Responsibilities

• Deployment: Deploy and configure data science software for new clients across AWS, Azure, GCP, and on-premise environments.
• Support & Maintenance: Provide ongoing technical support, monitor health and performance, apply patches and upgrades, troubleshoot issues.
• Client Liaison: Act as a technical point of contact for clients on deployment and support matters, scope infrastructure requirements.
• Internal Collaboration & Process Improvement: Contribute to tooling, automation, and documentation to improve deployment speed and repeatability.

Skills

DevOps / infrastructure

Cloud platforms

Infrastructure-as-Code

Linux

Networking

Troubleshooting

Tools

Terraform

Ansible

Docker

Kubernetes

Grafana

Job description

Job Purpose

The Engineer is responsible for deploying, configuring, and maintaining data science software, e.g. Posit for Jumping Rivers' clients across cloud and on-premise environments. The role combines hands‑on infrastructure delivery with ongoing technical support, ensuring client systems are deployed to a high standard and remain stable, secure, and performant once live. You will work closely with clients and the wider Engineering team to deliver reliable infrastructure.

Key Responsibilities

• Deployment
  • Deploy and configure data science software for new clients across AWS, Azure, GCP, and on-premise environments
  • Provision infrastructure using Infrastructure-as-Code tools (e.g. Terraform, Ansible)
  • Configure authentication, SSO, and access control integrations (e.g. LDAP, SAML, OAuth)
  • Set up networking, security, and compliance configurations (VPCs, firewalls, SSL/TLS)
  • Document deployment architecture and configuration for each client environment
• Support & Maintenance
  • Provide ongoing technical support for client environments, responding to and resolving support tickets
  • Monitor system health, performance, and availability across client deploymentsApply patches, upgrades, and version updates to data science software and underlying infrastructure
  • Troubleshoot and resolve infrastructure, networking, and application‑level issues
  • Escalate and coordinate with third‑party support where required
• Client Liaison
  • Act as a technical point of contact for clients on deployment and support matters
  • Scope infrastructure requirements for new deployments in collaboration with clients
  • Communicate technical issues, fixes, and maintenance work clearly to non‑technical stakeholders
  • Support onboarding of new clients onto systems
• Internal Collaboration & Process Improvement
  • Contribute to internal tooling, automation, and documentation to make deployments faster and more repeatable
  • Share knowledge with the wider Engineering team on deployment best practice and recurring issues

Technical Skills

• Essential
  • Experience in a DevOps, infrastructure, or systems engineering role
  • Hands‑on experience with at least one major cloud provider (AWS, Azure, or GCP)
  • Experience with Infrastructure-as-Code (Terraform, Ansible, or similar)
  • Comfortable working in Linux environments
  • Understanding of networking fundamentals (DNS, load balancing, VPNs, firewalls)
  • Strong, methodical troubleshooting skills
• Desirable
  • Direct experience deploying or administering data science software
  • Familiarity with R and/or Python ecosystems
  • Experience with containerization (Docker/Kubernetes)
  • Scripting experience (Bash, Python) for automation
  • Experience with monitoring/observability tooling (Grafana or similar)

Soft Skills

• Experience working in a consultancy or client‑facing environment
• Excellent communication skills, with the ability to explain technical issues to non‑technical clients
• Ability to manage multiple client deployments and support requests concurrently
• Can demonstrate initiative and ownership of tasks
• Experienced in owning delivery of individual work from start to finish