SVP – Cyber Technology Engineer

4 months ago

Base Salary

$120k - $253k/yr

Responsibilities

Design, engineer, and scale enterprise data-ingestion pipelines for cyber platforms, including Splunk.
Lead onboarding and integration of application, infrastructure, Kubernetes, and cloud-native data sources.
Engineer ingestion mechanisms using HEC, Universal Forwarders, syslog, forwarders, and edge-processing layers.
Enable Kubernetes-based logging and observability integrations across containerized environments.
Integrate cyber data platforms with Azure and modern application architectures.
Improve data quality, normalization, consistency, performance, and reliability across distributed systems.
Design automation and configuration-management solutions using DevOps practices.
Support incident response, escalation, post-mortem analysis, system design, platform management, and capacity planning.
Research, document, and present engineering solutions and architectural improvements.
Collaborate across global teams to develop scalable self-service onboarding and mentor junior engineers.

Bachelor of Science degree in Computer Science, Information Systems, or a related technical field involving systems coding or engineering, or equivalent work experience.
Strong experience with large-scale data platforms, preferably Splunk, with ELK or Kafka accepted as alternatives.
Deep expertise in Kubernetes and containerized environments, including logging and observability integration.
Strong knowledge of cloud platforms, preferably Azure, and hybrid on-premises and 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 Python, Go, Java, or similar programming languages.
Experience with configuration management and infrastructure as code, including Ansible or Terraform.
Strong understanding of Linux systems, networking, system internals, APIs, and event-driven architecture.
Experience troubleshooting, debugging, optimizing, and performance-tuning large-scale distributed systems and data pipelines.
Familiarity with CI/CD, modern DevOps practices, enterprise logging and observability, data modeling, log normalization, schema design, security technology integration, and cloud-native architecture.
Understanding of risk culture, system controls, and risk-reduction techniques.
Exposure to AI/ML use cases on large-scale datasets is valuable.

Competitive compensation, benefits, and wellbeing programs.
Flexible global resources and tools supporting health, personal resilience, and financial goals.
Generous paid leaves, including paid volunteer time.
Equal Employment Opportunity/Affirmative Action workplace.
Role based in New York City, NY.

10,000+ employees