Shashank Shekhar Rajhans
Technical Support Specialist @ ARIS GmbH | Data Analyst | Power BI Engineer | SQL, Data Modeling & ETL | McKinsey Forward Graduate
Chennai, Tamil Nadu
shashankshekharrajhans1999@gmail.com
I'm a Technical Support Specialist with solid hands-on experience bridging the gap between deep technical troubleshooting and business operations. Currently at ARIS GmbH, I specialize in resolving complex enterprise support issues, handling system diagnostics, and working closely with product and engineering teams to ensure high platform reliability and customer satisfaction. Before this, I worked at Cognizant Technology Solutions as a Software Developer. That background in core software development gives me a strong technical foundation—allowing me to read code, write custom scripts, debug root causes at the stack level, and communicate effectively with software engineering teams. What drives me is solving high-stakes technical problems at scale while delivering an effortless user experience. I’ve always admired Google’s culture of innovation and engineering excellence, and I’m eager to bring my hybrid background in development and technical support to the team here.
Technical Support Engineer — Client-Facing Technical & Application Support
ARIS GmbH
- • Serve as primary technical support point of contact for 20+ enterprise clients, troubleshooting and resolving complex product and system issues while sustaining 98% SLA compliance.
- • Diagnose and resolve technical incidents across 15+ global accounts through structured root-cause and benchmarking analysis, reducing incident recurrence by 25–30% and improving system throughput by 25%.
- • Build and maintain 20+ Power BI and SQL-based support dashboards, converting multi-system technical data into actionable insights for 50+ stakeholders and cutting ad-hoc support requests by 35%.
- • Lead 20+ technical support workshops and case reviews with clients and cross-functional Engineering, Sales, and Operations teams to troubleshoot issues, validate fixes, and align on resolution roadmaps.
- • Identify and resolve 12+ recurring technical and process bottlenecks through structured diagnostics, cutting manual remediation effort by 40%.
- • Automate recurring technical support and reporting workflows using Python and SQL, improving case turnaround time by 25% and reducing manual troubleshooting by 40%.
- • Performer of the Quarter — ARIS GmbH, 2025
Software Engineer (Production Support) — Enterprise Customer Solutions
Cognizant Technology Solutions
- • Acted as primary technical contact for enterprise customers, troubleshooting product and system issues and delivering data-backed resolutions to complex technical challenges.
- • Performed technical and process root-cause analysis on escalated support cases, identifying fixes that reduced errors by 20% and improved system throughput by 25%.
- • Built self-service diagnostic dashboards and reporting tools for enterprise stakeholders, reducing repeat ad-hoc technical support inquiries by 35%.
- • Managed cross-functional technical escalations, coordinating with Engineering, Support, and Operations teams to drive timely case resolution and maintain customer trust.
- • Partnered with Sales and Operations to translate customer-reported issues into structured technical support and process-improvement recommendations, backed by 20+ requirement-gathering workshops.
AI-driven Automated Ticket Triage and Routing System
Tech Stack: Python, LangChain, OpenAI API, ServiceNow API, FastAPI, Docker Description: Built an end-to-end intelligent routing pipeline that ingests incoming support tickets in real-time, extracts intent and urgency using LLMs, and categorizes them with 94% accuracy. Integrated the model with ServiceNow to automatically assign tickets to the appropriate tier-2/tier-3 teams, reducing mean time to acknowledge (MTA) by 45%.
Automated Root Cause Analysis (RCA) and Log Summarizer
Tech Stack: Python, Streamlit, Anthropic Claude API, ELK Stack (Elasticsearch, Logstash, Kibana) Description: Created an internal dashboard that interfaces with ELK logs during high-severity incidents. When triggered by an engineer, the tool parses multi-gigabyte stack traces and error logs, filters out noise, and generates a structured, human-readable RCA draft with probable failure points and remediation scripts in under 30 seconds.
B.Tech
SRM Institute of Science and Technology · 84%
Microsoft Certified: Azure Administrator (AZ-104)
Microsoft
Jun 2024Certified ARIS Process Mining Professional
Software AG
Jul 2026
Attendee · Oct 24, 2026