9 of 9 Azure AKS Jobs in Yorkshire

code (IAC) in Azure. As a Senior Cloud Engineer, you will be part of a supportive and skilled team responsible for delivering change to our public cloud (Microsoft Azure). The role requires skills and experience across the Microsoft Azure stack to enable the successful automation, monitoring and management of our Azure environment. Utilising … Engineering team, consisting of 6 engineers delivering change for the business using SAFe and Agile. The team focuses on modernising existing systems and building new platform solutions in Azure, while supporting other product teams across the business. What's In It For You? Skipton values work/life balance and we are proud to support hybrid and flexible …/security tools like Azure Monitor, Policy, and Defender for Cloud. Desirable: Experience with python scripting and containerisation technologies such as Kubernetes, Azure Kubernetes Service (AKS), App services and Azure SQL. Agile-minded, optimistic, passionate, and pragmatic about delivering value to customers. A collaborative mindset, with the ability to take ownership of tasks More ❯

plus a data-driven mindset for analysing IAM logs and evaluating risk. On the cloud side, they must understand IAM constructs in AWS (users, roles, policies, permission boundaries), Azure (Azure AD, RBAC, PIM), GCP (principals, roles, policy bindings), and Alibaba Cloud (RAM users, groups, roles, and policy management), as well as how Kubernetes RBAC (roles, bindings … Identities Solid grasp of Kubernetes RBAC entities—Role, Cluster Role, Role Binding, ClusterRoleBinding—and how they map to Kubernetes API groups. Awareness of how cloud-provider-managed Kubernetes (EKS, AKS, GKE) integrates with cloud IAM (for example, IAM Authenticator in EKS, GKE Workload Identity, Azure AD/Entra integration). SaaS Application Identity Management Familiarity with Single …/policies), Azure AD & RBAC, and GCP IAM (roles/bindings). Familiarity with Kubernetes RBAC (Role Bindings, ClusterRoleBindings) and how those ties into cloud IAM (EKS, AKS, GKE). Proven track record analysing SaaS-based identity integrations (e.g., SAML SSO, SCIM provisioning). Strong gap-analysis skills, able to pinpoint missing or weak access controls. Comfortable More ❯

plus a data-driven mindset for analysing IAM logs and evaluating risk. On the cloud side, they must understand IAM constructs in AWS (users, roles, policies, permission boundaries), Azure (Azure AD, RBAC, PIM), GCP (principals, roles, policy bindings), and Alibaba Cloud (RAM users, groups, roles, and policy management), as well as how Kubernetes RBAC (roles, bindings … grasp of Kubernetes RBAC entities-Role, Cluster Role, Role Binding, Cluster Role Binding-and how they map to Kubernetes API groups. Awareness of how cloud-provider-managed Kubernetes (EKS, AKS, GKE) integrates with cloud IAM (for example, IAM Authenticator in EKS, GKE Workload Identity, Azure AD/Entra integration). SaaS Application Identity Management: Familiarity with Single … Azure AD & RBAC, and GCP IAM (roles/bindings). Familiarity with Kubernetes RBAC (Role Bindings, Cluster Role Bindings) and how those ties into cloud IAM (EKS, AKS, GKE). Proven track record analysing SaaS-based identity integrations (e.g., SAML SSO, SCIM provisioning). Strong gap-analysis skills, able to pinpoint missing or weak access controls. Comfortable More ❯

plus a data-driven mindset for analyzing IAM logs and evaluating risk. -On the cloud side, they must understand IAM constructs in AWS (users, roles, policies, permission boundaries), Azure (Azure AD, RBAC, PIM), GCP (principals, roles, policy bindings), and Alibaba Cloud (RAM users, groups, roles, and policy management), as well as how Kubernetes RBAC (roles, bindings … Identities Solid grasp of Kubernetes RBAC entities—Role, Cluster Role, Role Binding, ClusterRoleBinding—and how they map to Kubernetes API groups. Awareness of how cloud-provider-managed Kubernetes (EKS, AKS, GKE) integrates with cloud IAM (for example, IAM Authenticator in EKS, GKE Workload Identity, Azure AD/Entra integration). SaaS Application Identity Management Familiarity with Single …/policies), Azure AD & RBAC, and GCP IAM (roles/bindings). Familiarity with Kubernetes RBAC (Role Bindings, ClusterRoleBindings) and how those ties into cloud IAM (EKS, AKS, GKE). Proven track record analysing SaaS-based identity integrations (e.g., SAML SSO, SCIM provisioning). Strong gap-analysis skills, able to pinpoint missing or weak access controls. Comfortable More ❯

plus a data-driven mindset for analysing IAM logs and evaluating risk. On the cloud side, they must understand IAM constructs in AWS (users, roles, policies, permission boundaries), Azure (Azure AD, RBAC, PIM), GCP (principals, roles, policy bindings), and Alibaba Cloud (RAM users, groups, roles, and policy management), as well as how Kubernetes RBAC (roles, bindings … Solid grasp of Kubernetes RBAC entities—Role, Cluster Role, Role Binding, ClusterRoleBinding—and how they map to Kubernetes API groups. o Awareness of how cloud-provider-managed Kubernetes (EKS, AKS, GKE) integrates with cloud IAM (for example, IAM Authenticator in EKS, GKE Workload Identity, Azure AD/Entra integration). 5. SaaS Application Identity Management o Familiarity …/policies), Azure AD & RBAC, and GCP IAM (roles/bindings). • Familiarity with Kubernetes RBAC (Role Bindings, ClusterRoleBindings) and how those ties into cloud IAM (EKS, AKS, GKE). • Proven track record analysing SaaS-based identity integrations (e.g., SAML SSO, SCIM provisioning). • Strong gap-analysis skills, able to pinpoint missing or weak access controls. • Comfortable More ❯

API resilience. Nice to Have: Experience using PostgreSQL for data storage and management. Familiarity with Microsoft Azure , including Azure Virtual Machines, Azure CLI, AKS (Azure Kubernetes Service), and Azure DevOps. Experience working in agile teams delivering frequent releases to production. Additional Information: Location: Sheffield 3 days per week onsite More ❯

site in Sheffield. 🔒 The Opportunity: As the IAM Business Analyst, you will play a key role in assessing, mapping, and improving identity and access management processes across AWS, Azure, GCP, and Kubernetes platforms. You’ll work closely with technical teams, security SMEs, and stakeholders to drive analysis, identify gaps, and recommend least-privilege access models and IAM improvements. … essential. 🔧 Required Technical Expertise: Cloud-Specific IAM Experience (Must-Have): AWS IAM: Deep understanding of users, groups, roles, policies, SCPs; ability to audit and recommend least-privilege improvements. Azure Active Directory & RBAC: Knowledge of AD constructs, Conditional Access, PIM, and Azure RBAC. GCP … IAM: Strong grasp of principals, custom roles, bindings, and policy auditing at scale. Kubernetes RBAC: Knowledge of Role/ClusterRole Bindings and their integration with cloud-native IAM (EKS, AKS, GKE). SaaS IAM: Understanding of SSO (SAML, OAuth, OIDC), SCIM provisioning, and identity lifecycle management in tools like Office 365. ✅ Skills & Experience Required: 5+ years as a Business More ❯

software engineering best practice Experience with TDD (pytest or equivalent) Experience with cloud native deployments (currently in Databricks and Azure) Experience with Databricks Experience with managed endpoints, AKS or equivalent Experience with VCS Experience with CI/CD Proven track record of driving business growth and achieving targets Strong communication and negotiation skills Ability to think creatively More ❯

team. The primary focus is on building and maintaining the infrastructure to support the full data science lifecycle from data ingestion to model deployment, monitoring, and upgrades within Azure and Databricks environments. The engineer will work closely with data scientists in a collaborative, cross-functional setting, helping transition models from research into production. Key Responsibilities: Own and develop … models. Write clean, production-ready Python code. Apply software engineering best practices, CI/CD, TDD. Required Skills: Proficiency in Python, Databricks, and Azure. Experience with deployment tools (e.g., AKS, managed endpoints). Strong software engineering background (CI/CD, VCS, TDD). Ability to integrate ML into business workflows. Desirable: Background in quantitative disciplines (math, stats, physics). More ❯