JPMorgan Lead Infrastructure Engineer Network Operation 

Singapore 

466428069

Job responsibilities

1. Lead in-depth investigation into incidents originating from a Line of Business (LoB) Application Team or an Infrastructure Team (e.g., network, compute, or storage), security breaches,performance degradation, and outages to uncover the root causes. Utilize forensic methodologies and tools to gather evidence, reconstruct events using time-series data collected real-time during the incident, and analyze packet-based network traffic, NetFlow and/or SNMP data sources.
2. Conduct thorough examinations of network infrastructure, configurations, logs, and traffic patterns across processing tiers, On-Prem Data Centers, and Public Cloud Platforms (Azure, AWS & Google) to identify underlying issues and vulnerabilities. Collaborate with cross-functional multi-disciplinary teams to determine the root causes and contributing factors of incidents.
3. Apply advanced forensic techniques, including packet analysis, log analysis, memory forensics, and malware analysis, to extract relevant information and insights from network data.
4. Publish Findings, Analysis & Recommendation Deliverables:
   Write thoroughly clearly written formal papers for customer consumption and produce detailed reports for a broad audience including both infrastructure and application teams as well as business teams and leadership across all Lines of Business such as Treasury, Investment Banking, Digital, Retail or Corporate. Audience will include both technical and non-technical colleagues.
5. Develop and implement incident response procedures and protocols to effectively mitigate and contain network incidents. Provide guidance and support to incident response teams during critical incidents, ensuring timely resolution and minimal impact on business operations.
6. Analyze network performance metrics and trends to identify optimization opportunities and areas for improvement. Recommend and implement network enhancements, configurations, and upgrades to enhance performance, reliability, and security.
7. Stay abreast of industry standards, regulations, and best practices related to network security and forensic analysis. Ensure compliance with relevant security frameworks (e.g., NIST, ISO 27001) and assist in audits and assessments as needed.
8. Share expertise and insights with colleagues through training sessions, workshops, and knowledge-sharing platforms. Mentor junior team members and contribute to the continuous learning and development of the organization.

Required qualifications, capabilities, and skills

• Bachelor’s degree in computer science or related fields
• Minimally 5 years of networking infrastructure engineering or related experience
• Strong packet analysis expertise using a real-time application performance monitoring appliance such as Riverbed ARX, Live Action LiveNX or NetScout Infini Stream NG appliance as well as accompanying deep packet forensic tools such Riverbed Steel Central Transaction Analyzer or Live Action Live Capture.
• Provenexperience (5+ years) in network engineering, consulting, and forensic analysis roles, with a focus on incident response and root cause analysis.
• Experience with one or more large-scale enterprise network topologies including LAN, WAN, Wireless, Network Security. Examples include Routers (Cisco, Juniper, Arista) Switches (Cisco), Wireless (Cisco, Juniper), Transport (Cisco, Ciena). Firewall (Fortinet, Check Point, Cisco), Load Balancers (Cisco, F5), Proxy (Blue Coat), Public Cloud (AWS, Azure).
• Knowledge of CIDR and sub-netting (IPv4 and IPv6); IPv6 transition challenges; and generic solutions for network security features, including AWS WAF, intrusion detection systems (IDS), intrusion prevention systems (IPS), DDoS protection, and economic denial of service/sustainability (EDoS).
• Proficient in network forensic tools and appliances (e.g., Riverbed Steel Center Transaction Analyzer and Riverbed ARX, Wireshark, Splunk, Arista Packet Broker) and familiarity with scripting languages (e.g., Python, Perl) for automated analysis.
• Experience with one or more application performance management technologies (AppDynamics, Dynatrace).
• Strong knowledge of statistical techniques/concepts and experience applying them (regression, properties of distributions, statistical tests, etc).
• Experience with one or more observability, monitoring, and visualization tools (Grafana, Cortex, Splunk, ThousandEyes, DataDog and SevOne)
• Experience with interactive visualizations or dashboard frameworks such as Plotly / Dash is an added advantage. Familiarity with scientific computing Python libraries such as NumPy and data manipulation and analysis libraries such as Pandas.

• CCIE or equivalent certification