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SVP - Cyber Technology Engineer

At BNY, our culture allows us to run our company better and enables employees' growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world's investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.

Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance - and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary.

We're seeking a future team member for the role of SVP - Cyber Technology Engineer 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 

At BNY, our culture speaks for itself, check out the latest BNY news at:

BNY Newsroom

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 Here's a few of our recent awards: 

• America's Most Innovative Companies, Fortune, 2025
• World's Most Admired Companies, Fortune 2025
• "Most Just Companies", Just Capital and CNBC, 2025

Our Benefits and Rewards:

BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life's journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter. 

BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.

BNY assesses market data to ensure a competitive compensation package for our employees. The base salary for this position is expected to be between $120,000 and $253,000 per year at the commencement of employment. However, base salary if hired will be determined on an individualized basis, including as to experience and market location, and is only part of the BNY total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, short and long-term incentive packages, and Company-sponsored benefit programs. 
This position is at-will and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation) at any time, including for reasons related to individual performance, change in geographic location, Company or individual department/team performance, and market factors.