Satish Kumar Paswan

• Remodeled Linux-based infrastructure, cutting system downtime by 20% for critical applications and boosting overall system performance scores by 15% across 200+ servers, thereby modernizing processes.
• Pioneered AI-based incident management by implementing Moogsoft, resulting in a 60% reduction in mean time to resolution and improving system uptime to 99.99% per quarter.
• Championed the creation of a comprehensive knowledge base, mentoring 5+ junior administrators in resolving Level 1 issues; served as the single point of contact for critical escalations.
Diagnosed and rectified over 150 system-related issues monthly, leveraging the Remedy ticketing system to streamline resolution processes and maintain optimal system performance, ensuring uninterrupted workflows for end-users.
• Facilitated seamless communication between technical teams by implementing detailed documentation of 50+ recurring system errors within the Remedy platform, minimizing downtime.
• Revamped Veritas Cluster Manager processes for 15+ Linux clusters, cutting recovery time objective (RTO) by 30 minutes, ensuring minimal disruption through the avoidance of data loss, and improving system resilience.
• Reconfigured Veritas Cluster Manager service management routines, resulting in faster recovery times after system disruptions, leading to recognition from senior management as the 'fastest recovery time" across all L1 teams.
• Revamped Linux server security protocols by implementing rigorous patch management strategies and promptly installing 50+ security updates, bolstering system resilience against potential zero-day exploits.
• Championed daily stand-up meetings that improved awareness of system status and dependencies across teams resulting in a 20% reduction in server downtime and the most collaborative team in the company.
• Revamped patching process for 50+ Linux servers leveraging Ansible playbooks, reducing security vulnerabilities by 25% and streamlining deployment times by 40%, freeing up 10 hours per week for the team to focus on higher priority projects.
• Fortified system stability through vigilant monitoring of cluster resources, resolving 9 server performance bottlenecks weekly and implementing automated scripts and configurations that saved 8 hours of manual intervention, while strictly adhering to SLAs.
• Scrutinized Linux server disk space utilization across 50+ servers, predicting storage needs and advocating for upgrades that prevented potential performance bottlenecks by 30% over six months.
• Pinpointed and rectified 25+ critical physical server malfunctions using HPSIM/ILO/HP OneView consoles, ensuring zero data loss and preventing potential system downtime incidents for 5000+ users.
• Secured uninterrupted infrastructure operations; collaborated with HP, RedHat, and Veritas, expediting hardware replacements and resolving 50+ critical system failures within designated SLAs, upholding system stability.
• Fortified network defenses by configuring and managing firewalls, intrusion detection/prevention systems, and security protocols leading to a 40% reduction in security incidents and unauthorized access attempts annually.
• Pinpointed root causes of complex technical issues using advanced diagnostic tools and shell scripting, leading to faster problem resolution and elevating overall system reliability by 75%.
• Spearheaded the migration of 20 virtual machines to AWS and Azure, enhancing system resilience by 40% and slashing infrastructure maintenance downtime to under 2 hours per month.
• Deployed Ansible playbooks on 50+ servers, cutting down deployment times by 60% and speeding up system updates from 8 hours to a mere 2 hours through automation.
• Automated data preprocessing pipelines with Python and Pandas, building tools that processed datasets including 1000+ data points and improving the data science team's model training speed as the most junior member on the team.
• Pioneered machine learning model for predictive maintenance using scikit-learn and TensorFlow, resulting in selection as the only intern to present findings to fix the three biggest causes of crashes.

• Dedicated full-time research assistant with significant contributions to projects in computer science and engineering.
• Conducted comprehensive research on object detection methodologies.
• Skillfully gathered and organized research data, creating visual aids (graphs and charts) to support presentation findings.
• Collaborated productively in a dynamic laboratory environment, demonstrating adaptability and teamwork.