Data Streaming

Capgemini 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: 340000 team members in more than 50 countries
• Heritage: Over 55 years of trusted expertise
• Services: End-to-end solutions from strategy and design to engineering
• Core Capabilities: AI Generative AI Cloud Data and deep industry expertise
• 2024 Global Revenue: 22.1 billion

As 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.

• Design provision and maintain Kubernetes clusters across cloud on-premises and hybrid environments
• Monitor cluster performance and optimize resource utilization
• Troubleshoot issues and implement solutions to ensure high availability and stability

• Manage Splunk infrastructure (indexers search heads)
• Troubleshoot ingestion issues latency and indexing delays
• Develop and maintain SPL queries saved searches alerts and dashboards
• Perform capacity planning performance tuning and upgrade planning
• Implement data onboarding strategies and field extractions for new log sources

• (Preferred) Experience with Cribl
• Design build and optimize Cribl pipelines for log routing transformation filtering and enrichment
• Integrate Cribl with various data sources and destinations
• Automate pipeline deployments and configuration using CI/CD and GitOps practices

• Participate in incident response and resolution to minimize downtime
• Continuously analyze and improve performance reliability and security of production environments

• Bachelors degree in Engineering Computer Science IT or related field
• Minimum 5 years of professional experience
• Excellent English communication skills (verbal and written)

Technical Expertise:

• Kubernetes: Deep understanding of architecture concepts and best practices; hands-on experience managing clusters at scale
• Splunk or ELK: Experience with log data platforms data organization and analysis
• GitLab: Familiarity with CI/CD features and pipeline scripting
• Cloud Platforms: AWS Azure GCP experience
• Troubleshooting: Strong problem-solving and root cause analysis skills

Soft Skills:

• Strong collaboration and communication skills
• Ability to work effectively with cross-functional teams