Azure Cloud Engineer

Jumping Rivers is an analytics company whose passion is data and machine learning. We help our clients move from data storage to data insights.The company has three key strands: training, data engineering and machine learning consultancy. As a small company, the roles are rarely clear cut. We think this is a

good

thing; the team get to experience different ideas and concepts, never stuck on mundane tasks.We are based in Newcastle upon Tyne in the Catalyst Building - home to the National Innovation Centre for Data. But half the company is remote (within the UK). We trust our team to manage their own time. If you want to go for a run in the afternoon and work later, that's fine with us!If you are based near Newcastle, then you can come into our office.Up to £1,000 on the cycle to work scheme25 days holiday + statutory holidaysAdditional holidays three yearsAdditional employer pension contributionOpportunities to attend and present at conferencesPrivate medical insuranceWe embrace flexibility and remote working. If you want to take Friday afternoon off and work the next day, that's fine. We even allow you to be flexible with Bank holidays. If you want to work on Bank holiday and use that day some other time; that's also fine!Job Description

We are seeking a skilled Cloud Engineer to maintain and support both our clients’ and internal cloud infrastructure. We are a Data Science & Engineering consultancy looking to expand our Azure and Kubernetes expertise. You will be responsible for ensuring the performance, security, and reliability of both internal and clients’ systems while identifying opportunities for improvement. You will design and implement suitable architectures for scalable data science environments.Key Responsibilities:Design and deploy secure, high-performance solutions on the Azure cloud platform for our clients.Manage both internal and clients’ Azure infrastructure including virtual machines, storage, and networking.Develop and maintain internal and external Infrastructure as Code (IaC) using Terraform, or Ansible.Build and manage CI/CD pipelines in Azure DevOps and GitLab CI.Monitor cloud performance and ensure security compliance.Troubleshoot cloud infrastructure issues and assist in cloud migration efforts.Develop the Engineering’s teams Azure knowledge and capabilities.Preferred Experience

Required Experience:3+ years of hands-on experience as a Cloud Engineer or in a similar cloud-focused role.Expertise in Microsoft Azure, with a deep understanding of key services like Azure Virtual Machines, Azure Kubernetes Service (AKS), Azure Storage, Azure Networking, Active Directory, and Azure DevOps.Strong experience with Kubernetes for container orchestration, including deployment, scaling, and management of containerised applications.Proven experience in designing scalable cloud architectures for data-intensive applications, including data science platforms and environments.Solid understanding of Infrastructure as Code (IaC) with tools like Terraform, ARM templates, or Ansible for automating cloud infrastructure.Experience managing Active Directory (AD) integrations on Linux environments, including RedHat/Ubuntu, as well as handling Azure AD Connect and hybrid identity management across cloud and on-premise systems.Proficiency in cloud security best practices (identity management, role-based access control, security policies) and experience with cloud monitoring and performance optimisation.Hands-on experience with CI/CD pipelines and automation tools, preferably using Azure DevOps, GitLab CI, or similar tools.Experience with driving continuous improvement and providing guidance to others.Excellent communication and stakeholder management skills.Preferred Experience:Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.Azure certifications such as Azure Solutions Architect Expert, Azure Administrator, or Azure DevOps Engineer.Proficiency in scripting languages such as Python, Bash, or R for automating cloud processes.Familiarity with big data tools like Posit, Databricks, Snowflake, Azure Data Lake, Apache Spark, or Hadoop in cloud environments.Experience with cloud-native data pipelines and tools for ETL, data processing, or machine learning workloads.Familiarity with multi-cloud environments (e.g., AWS, Google Cloud) and hybrid cloud strategies.Knowledge of cloud cost optimisation strategies and best practices for managing resources in multi-cloud setups.

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