Highly motivated Computer Science graduate and Data Engineer with hands-on experience in building robust distributed data systems, cloud platforms, and AI-driven solutions. Proven ability to develop and optimize ETL pipelines, integrate machine learning models with knowledge graphs, and enhance system reliability through advanced automation and monitoring. Eager to leverage strong analytical, debugging, and problem-solving skills to drive innovation in Platform Engineering, DevOps, and applied AI.
Data Engineer
Noida, Uttar Pradesh, India
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Summary
Currently leading cloud-based ETL pipeline development and optimization to support critical enterprise analytics platforms and ensure data integrity.
Highlights
Developed and maintained robust cloud-based ETL pipelines, ensuring seamless data flow and integration for diverse enterprise analytics platforms.
Implemented rigorous SQL validation and comprehensive monitoring protocols, significantly improving data accuracy and reliability by identifying and rectifying data inconsistencies.
Proactively analyzed system logs and performance dashboards to detect and resolve critical workflow issues, enhancing platform stability and reducing potential downtime.
Contributed to operational excellence by providing detailed documentation and conducting in-depth root-cause analysis, streamlining processes and reducing recurring system incidents.
Leveraged Snowflake and advanced ETL orchestration tools to optimize data processing workflows, achieving greater efficiency and scalability for large datasets.
Graduate Engineer Trainee - Test Automation
Noida, Uttar Pradesh, India
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Summary
Designed and implemented automated test frameworks to ensure software quality and reliability across various applications.
Highlights
Developed robust automated test frameworks using Java, Selenium, and TestNG, significantly increasing test coverage and accelerating software release cycles.
Architected structured test flows for comprehensive functional and regression testing, reducing manual testing effort and improving defect detection rates.
Conducted in-depth failure analysis via debugging, log analysis, and scenario tracing, decreasing defect resolution time and enhancing overall software stability.
Research Intern
Noida, Uttar Pradesh, India
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Summary
Developed an innovative smart-home activity inference system leveraging machine learning and knowledge graphs.
Highlights
Pioneered the development of a smart-home activity inference system, integrating machine learning and knowledge graphs to achieve high accuracy in real-time activity detection.
Constructed a comprehensive knowledge graph in Memgraph, meticulously modeling entities and relationships for efficient data representation and retrieval using Cypher queries.
Seamlessly integrated knowledge graph outputs with machine learning models, enhancing the precision and speed of real-time activity inference for advanced smart-home applications.
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Bachelor of Engineering
Computer Science (Hons. Internet of Things)
Grade: CGPA: 7.94 / 10
Published by
Academic Research
Summary
Developed and analyzed analytics-driven systems designed to enhance student engagement and learning outcomes in smart classroom environments.
Published by
Academic Research
Summary
Explored the transformative effects of generative AI on various industries, analyzing its implications for job markets and technological advancements.
Published by
Academic Research
Summary
Investigated the critical cybersecurity vulnerabilities and opportunities presented by the advent of quantum computing technologies.
Python, JavaScript, Java, SQL.
Snowflake, Linux, Docker, Git, CI/CD concepts, Distributed Data Systems.
Workflow Orchestration, Monitoring, Log Analysis, Automation, System Reliability.
ML Model Integration, Knowledge Graph Workflows, Intelligent Automation, Generative AI.
ETL Pipelines, Data Validation, Debugging, Workflow Optimization.
Node.js, REST APIs, GraphQL.
Memgraph, Cypher Queries, Graph Modeling.
Troubleshooting, Scripting, Security Fundamentals, Analytical Thinking.
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Summary
Engineered a full-stack JavaScript dashboard for visualizing classroom interaction metrics and real-time participation data.
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Summary
Designed and implemented an IoT-based automation system using sensors and RFID to improve monitoring and energy efficiency.