Summary
What you’ll impact
The SVP – Cyber Technology Engineer will design, engineer, and scale enterprise data ingestion pipelines for cyber platforms, lead integration of data sources, and drive automation and operational excellence across distributed systems. The role requires deep expertise in Kubernetes, cloud platforms, and large‑scale data platforms, and involves mentoring junior engineers and collaborating globally.
Responsibilities
What you'll do
- Design, engineer, and scale enterprise data ingestion pipelines for cyber platforms, including Splunk
- Lead onboarding and integration of application, infrastructure, (especially Kubernetes and cloud-native) data sources
- Engineer and optimize ingestion mechanisms including HEC, (Heavy) forwarders, syslog, and edge processing layers
- Enable Kubernetes-based logging and observability integrations across containerized environments
- Integrate cyber data platforms with cloud services (Azure) and modern application architectures
- Improve data quality, normalization, and consistency across large-scale distributed systems
- Mitigate systemic outages and reliability risks across critical cyber technology platforms
- Analyze complex technical issues and implement scalable solutions across distributed environments
- Design and implement automation and configuration management solutions using DevOps practices
- Contribute to incident response, escalation support, and post-mortem analysis
- Support system design, platform management, and capacity planning for ingestion and data services
- Drive operational excellence and continuous improvement across the platform
- Research, document, and present engineering solutions and architectural improvements
- Collaborate across global teams to enable a scalable, self-service onboarding model
- Mentor and guide junior engineers and contribute to team capability uplift
Requirements
What you’ll bring
- Bachelors of Science degree in Computer Science/Information Systems or related technical field involving systems coding/engineering, or equivalent work experience
- Strong experience with large-scale data platforms (Splunk preferred, ELK/Kafka or similar acceptable)
- Deep expertise in Kubernetes and containerized environments, including logging and observability integration
- Strong knowledge of cloud platforms (Azure preferred) and hybrid (on-prem + cloud) architectures
- Experience designing and operating data ingestion pipelines and distributed systems
- Hands-on experience with:
- Universal Forwarders, HEC, syslog, or similar ingestion technologies
- Proficiency in one or more of the following: Python, Go, Java, or similar programming languages
- Experience with configuration management and infrastructure-as-code (Ansible, Terraform, etc.)
- Strong understanding of Linux systems, networking, and system internals
- Experience troubleshooting large-scale distributed systems across complex networks
- Experience integrating systems using APIs and event-driven architecture
- Familiarity with CI/CD and modern DevOps practices
- Solid understanding of risk culture, system controls, and risk reduction techniques