Incident Response Cyber Security

Sunny Khanorkar Cyber Security Engineer

*****@*************.*** 571-***-**** USA LinkedIn

Summary

Cybersecurity Engineer with 2+ years of strong expertise in implementing and managing security solutions to protect enterprise systems and data. Skilled in using a wide range of security tools, including SIEM, IDS/IPS, cloud security solutions, and vulnerability management platforms. Experienced in automating incident response, improving threat detection, and ensuring compliance with industry sta ndards. Proficient in scripting, cloud infrastructure, and collaborating with cross-functional teams to develop and enforce security protocols. Passionate about reducing risk, improving security posture, and staying ahead of emerging threats. Technical Skills

Security Tools: Splunk, AWS CloudWatch, AWS GuardDuty, AWS Security Hub, ServiceNow, Snort, Suricata, Microsoft Defender for Cloud, Azure Sentinel, ELK Stack

Scripting & Programming: Python, Bash, scikit-learn, TensorFlow

Compliance & Standards: NIST, ISO/IEC 27001, PCI DSS, SOC 2

Cloud & Infrastructure: AWS, Azure, Microsoft Defender for Cloud

Incident Response: SIEM tools, IDS/IPS, Threat Intelligence platforms

Collaboration & Automation: Agile Methodologies, Runbooks, Incident Triage, Automated Alerting, Automated Ticketing Professional Experience

Cyber Security Engineer, LendingClub 10/2024 - Present Remote, USA

Worked on the Security Incident Response Automation project by collaborating with IT, DevOps, and compliance teams. Led requirement gathering sessions to align with business needs, combining Agile methods for iterative development and feedback.

Steered a broad analysis of existing security incident response processes, finding gaps in automation and incident triage. Worked to define automated workflows using SIEM tools like Splunk and threat intelligence platforms, reducing incident response times by 30%.

Developed custom scripts in Python and Bash to automate data collection, alerting, and preliminary incident analysis, reducin g the manual workload and response time. Integrated with existing systems such as ServiceNow for automated ticketing and escalation.

Ensured the automated security response solution adhered to industry standards such as NIST and ISO/IEC 27001. Conducted regular audits to ensure compliance with internal security policies and regulatory frameworks, including PCI DSS and SOC 2.

Integrated the automated incident response system with real-time monitoring tools such as AWS CloudWatch, AWS GuardDuty, and AWS Security Hub to enhance visibility into network traffic, system health, and anomalous behaviors across LendingClub’s infrastructure, improving threat detection by 25%.

Collaborated with diffrent teams, involving legal and risk management, to document incident response procedures, create runbooks, and establish clear escalation protocols. Acted tabletop exercises to ensure all teams were aligned on incident handling protocols. Associate Cyber Security Engineer, NTT DATA 06/2021 – 08/2023 Maharashtra, India

Collaborated with cross-functional teams including network engineers, IT, and threat intelligence groups to gather project requirements, ensuring the design of a tailored network traffic analysis system aligned with both security protocols and organizational goals.

Designed the network traffic analysis system architecture, team up closely with data scientists and network specialists to incorporate ML models that detect abnormal patterns, integrating seamlessly with existing network infrastructures and security solutions.

Worked with the incident response team to use Intrusion Detection and Prevention Systems (IDS/IPS) like Snort and Suricata, easing response time to incidents by 30% by ensuring the system was configured for real-time monitoring, detection, and response.

Leveraged Microsoft Defender for Cloud and Azure Sentinel to monitor cloud-based workloads, set up custom detection rules, and correlate threat signals across the Azure environment, enhancing visibility and reducing undetected anomalies by 28%.

Partnered with machine learning specialists to develop and fine-tune models for anomaly detection using Python (scikit-learn, TensorFlow), improving detection accuracy by 25% by continuously training algorithms with updated network data.

Coordinated with the SOC to configure automated alerting systems using Splunk and the ELK stack, enabling timely notifications, anomaly visualization, and real-time threat response capabilities, reducing manual workload for the security team by 40%.

Cooperated with the penetration testing and red team groups to conduct exhaustive testing and threat simulations, ensuring the network traffic analysis system’s resilience against emerging vulnerabilities, and fine-tuning detection mechanisms based on feedback from security drills.

Education

Virginia Polytechnic Institute and State University (Virginia Tech) Falls Church, VA, USA Master of Engineering in Computer Engineering 08/2023 – 05/2025 Rajiv Gandhi College of Engineering and Research (Nagpur University) Nagpur, India Bachelor of Engineering in Computer Science Engineering 07/2018 – 07/2022

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