SVP Director- CyberTech

In this role, you ll make an impact in the following ways: In this role, you ll make an impact in the following ways: Design, engineer, and scale enterprise data ingestion pipelines for cyber platforms, including Splunk. To be successful in this role, we re seeking the following: Bachelors of Science degree in Computer Science/Information Systems or related technical field involving systems coding/engineering, or equivalent work experience.

GTD ID: PGTE9Z
Role: Director - Cyber Platform (Splunk/Kubernetes/Azure)
Rate: ***/hour all inclusive
Location: On-Site in New York City, NY 4 days a week

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Description and Location
Job Description
SVP/Director Cyber Technology Platform
We re seeking a future team member for the role of SVP/Director Cyber Technology Platform to join our Technology Information Security Division Cyber Technology team. This role is in New York City, NY.
In this role, you ll make an impact in the following ways:
In this role, you ll make an impact in the following ways:
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
To be successful in this role, we re seeking the following:
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
Other supplemental valuable expertise/experience:
Experience with enterprise logging and observability platforms
Familiarity with data modeling, normalization, and schema design for log data
Experience integrating security technologies (SIEM, EDR, vulnerability platforms, etc.)
Exposure to AI / ML use cases on large-scale data sets
Experience with distributed systems design and performance optimization
Debugging and optimizing large-scale systems and data pipelines
Experience with containerization technologies and cloud-native architecture
Strong preference for CI/CD and DevOps-driven engineering practices