Data Streaming

About Capgemini

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: 340,000 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

Position: Data Streaming Engineer

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.

Key Responsibilities

1. Kubernetes Infrastructure Management

• 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

2. Splunk Operations & Engineering

• 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

3. Cribl Pipeline Management

• (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

4. Production Support

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

Qualifications

• Bachelor’s 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