
Timeline
About me
Software Engineer @CiscoAppDynamics | Immediate Joiner | Former SDE Intern @Ericsson | JAVA | Python | Backend | Full Stack | PESU '23
Education

The gurukul, panchkula, harayana
2015 - 2017Cbse 10 cgpa
Pes university, banglore
2019 - 2023Bachelor of technology - btech computer science
Step by step high school, jaipur
2010 - 2015Cbse
Experience

Ericsson
Jun 2022 - Jul 2022Summer intern• Configured and Streamlined data pipeline to efficiently ingest and pre-process 82,000 images from MS-COCO dataset, successfully storing them in ElasticSearch Database. • Implemented image metadata extraction and tagging to enhance search relevance. • Designed and developed an image search engine website allowing users to query images under 200ms response time per query

Appdynamics
Jul 2023 - nowSoftware engineer•Real time Client data protection system 1. Designed and developed a Data Masking feature on AppDynamics Full Stack Observability (FSO), resulting in masking over 500,000 sensitive data entries from clients. 2. Utilized Kafka Streams stateful processing capabilities to dynamically apply transformation rules based on the data attributes and masking requirements improving data processing efficiency by 25% Impact: Enhanced client security and privacy contributing to a 15% increase in client trust and retention due to improved data security features. • Parsing of Logs 1. Co-developed a versatile Log Parsing feature of FSO that automatically detects and processes logs from various sources, including log4j, Logback, JSON, and infrastructure logs. 2. Implemented flexible parsing logic using Grok patterns and regex to handle diverse log sources and formats. Impact: Streamlined log management for 100+ clients, improving log processing reliability by reducing errors by 15% resulting in faster troubleshooting and higher customer satisfaction. • Developed Kafka Pipeline lag detecting tool Built a Real time lag detection system using Grafana dashboards, completely eliminating manual pipeline monitoring by automating the identification of MELT(Metrics, Events, Logs & Traces)data delays and bottlenecks. Impact: Improved system reliability by 25% through proactive lag monitoring, reducing data latency and enhancing pipeline stability in high-throughput environments. Show less
Licenses & Certifications
- View certificate

Udemy labs - online kubernetes lab for beginners - hands on
KodekloudJun 2023 - View certificate

Google cloud essentials
QwiklabsNov 2019 - View certificate

Baseline: data, ml, ai
QwiklabsOct 2019 - View certificate

Intermediate ml: tensorflow on gcp
QwiklabsOct 2019 - View certificate

Intro to ml: language processing
QwiklabsOct 2019 - View certificate

Bigquery for machine learning
QwiklabsOct 2019 - View certificate

Machine learning apis
QwiklabsOct 2019 
Drone computing
Pesu ioAug 2019
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