أبلاي إيدج ابدأ البحث عن عمل

Operations Engineer (SAS Admin & Kubernetes)

Hexaware Technologies · Dubai, United Arab Emirates

قدّم وتابع مع أبلاي إيدج
About the Role: We are looking for a skilled SAS Administrator / Kubernetes Operations Engineer to manage, maintain, and optimize our SAS platform environments deployed on containerized infrastructure. This role is primarily responsible for the administration, deployment, monitoring, and troubleshooting of SAS Viya/SAS 9 environments on Kubernetes, with a secondary responsibility of supporting SAS ETL operations to ensure smooth data pipeline execution.Key Responsibilities:Primary: SAS Administration & Kubernetes Operations (70%)Install, configure, and administer SAS Viya (and/or SAS 9.4) environments on Kubernetes clusters (on-prem or cloud — AWS/Azure/GCP).Manage containerized SAS deployments including Pods, Deployments, StatefulSets, Services, ConfigMaps, and Secrets.Perform day-to-day Kubernetes operations: cluster monitoring, scaling, upgrades, patching, and troubleshooting pod/container failures.Manage SAS Viya orchestration using Helm charts, Kustomize, and the SAS Viya 4 deployment tools.Monitor system health, resource utilization (CPU/memory/storage), and performance tuning of SAS environments.Handle user administration, license renewals, environment backups, and disaster recovery for SAS platforms.Troubleshoot SAS application/server issues including SAS Studio, SAS Environment Manager, SAS Compute Server, and CAS (Cloud Analytic Services).Manage ingress controllers, load balancers, persistent volumes, and namespace-level security/RBAC configurations.Apply patches, hotfixes, and version upgrades for SAS software in a Kubernetes-orchestrated environment.Implement and maintain monitoring/alerting solutions (e.g., Prometheus, Grafana, ELK/EFK stack) for SAS workloads.Secondary: SAS ETL Operations (30%): Support and monitor daily SAS ETL jobs, batch schedules, and data pipeline execution (SAS Data Integration Studio / SAS DI Studio, SAS Management Console).Troubleshoot ETL job failures, investigate log errors, and coordinate fixes with data engineering teams.Ensure data load consistency, job dependencies, and SLA adherence for scheduled ETL processes.Support performance tuning of SAS ETL jobs and optimize resource allocation on the SAS Grid/Compute environment.Coordinate with business/data teams for ETL enhancements, data validation, and issue resolution.Required Skills & Qualifications: 3–6 years of overall experience in SAS Administration, with hands-on exposure to Kubernetes-based deployments.Strong working knowledge of SAS Viya 3.x/4.x and/or SAS 9.4 architecture and administration.Hands-on experience with Kubernetes (kubectl, Helm, namespaces, RBAC, networking, storage/persistent volumes).Familiarity with containerization tools (Docker) and container registries.Experience with Linux/Unix system administration (shell scripting, cron, log analysis).Working knowledge of SAS ETL tools — SAS DI Studio, SAS Data Integration, SAS Management Console.Experience with monitoring/logging tools such as Prometheus, Grafana, Splunk, or ELK stack.Basic understanding of networking concepts (DNS, load balancers, ingress, firewalls) in a cloud/on-prem hybrid setup.Good understanding of SQL and relational databases (Vertica, SQL Server, PostgreSQL, etc.).Strong troubleshooting, analytical, and problem-solving skills.Good communication skills and ability to work with cross-functional teams (Infra, DevOps, Data Engineering).Preferred/Good to HaveSAS Administration or Kubernetes certification (CKA/CKAD).Experience with Terraform/Ansible for infrastructure automation.Experience working in regulated industries (BFSI, Healthcare, Pharma) where SAS is heavily used.Educational QualificationBachelor's/master’s degree in computer science, Information Technology, or a related field.Why Join UsOpportunity to work on modern SAS Viya + Kubernetes hybrid infrastructure.Exposure to both platform administration and data operations, broadening your skill set.Collaborative environment with cross-functional exposure to DevOps, Data Engineering, and Analytics teams.