Data Streaming

Long DescriptionAbout CapgeminiCapgemini is a global business and technology transformation partner, helping organizations accelerate their dual transition to a digital and sustainable world while creating tangible impact for enterprises and society.Global Presence: 340,000 team members in more than 50 countriesHeritage: Over 55 years of trusted expertiseServices: End-to-end solutions from strategy and design to engineeringCore Capabilities: AI, Generative AI, Cloud, Data, and deep industry expertise2024 Global Revenue: €22.1 billionPosition: Data Streaming EngineerAs a Data Streaming Engineer, you will build and maintain robust, scalable Kubernetes-based event streaming platforms. You will ensure reliability and efficiency in production and development environments, enabling smooth deployments and accurate event reporting.Key Responsibilities Kubernetes Infrastructure ManagementDesign, provision, and maintain Kubernetes clusters across cloud, on-premises, and hybrid environmentsMonitor cluster performance and optimize resource utilizationTroubleshoot issues and implement solutions to ensure high availability and stability Splunk Operations & EngineeringManage Splunk infrastructure (indexers, search heads)Troubleshoot ingestion issues, latency, and indexing delaysDevelop and maintain SPL queries, saved searches, alerts, and dashboardsPerform capacity planning, performance tuning, and upgrade planningImplement data onboarding strategies and field extractions for new log sources Cribl Pipeline Management(Preferred) Experience with CriblDesign, build, and optimize Cribl pipelines for log routing, transformation, filtering, and enrichmentIntegrate Cribl with various data sources and destinationsAutomate pipeline deployments and configuration using CI/CD and GitOps practices Production SupportParticipate in incident response and resolution to minimize downtimeContinuously analyze and improve performance, reliability, and security of production environmentsQualificationsBachelor’s degree in Engineering, Computer Science, IT, or related fieldMinimum 5 years of professional experienceExcellent English communication skills (verbal and written)Technical ExpertiseKubernetes: Deep understanding of architecture, concepts, and best practices; hands-on experience managing clusters at scaleSplunk or ELK: Experience with log data platforms, data organization, and analysisGitLab: Familiarity with CI/CD features and pipeline scriptingCloud Platforms: AWS, Azure, GCP experienceTroubleshooting: Strong problem-solving and root cause analysis skillsSoft SkillsStrong collaboration and communication skillsAbility to work effectively with cross-functional teams