Amit Yadav

I am a Grade 8 (Software Engineer III) specializing in Data Engineering on the NADP Team at Cisco. My expertise lies in designing and developing scalable data and ML-powered applications, contributing to all phases of application development, data engineering, architecture, and design. Our Cisco AI Network Analytics platform is a cornerstone for over 5,000 enterprise customers, managing 10 million APs and over 10 billion wireless clients. In my role, I am responsible for: • Designing ETL pipelines (DAGs) to process and transform raw telemetry data from various network entities. • Developing data and ML-powered insights and analytics, stored in PostgreSQL and OpenSearch, and visualized through a user-friendly UI. • Managing data engineering SDKs for writing data pipeline DAGs, scheduling, and running Spark jobs on AWS EMR clusters. • This SDK supports all infrastructure setup for Airflow DAGs, tasks for all DB operations, interaction with OS, S3, and utilities for app teams to easily build data pipelines. • Driving the Event Analytics project, which provides analytics for syslogs, client onboardings, and reachability events, becoming a new center of attraction for customers. • Designing and developing all backend Lambda functions for Event Analytics, which are used by the UI to trigger queries to OpenSearch. • Enhancing applications to include wired telemetry, attracting new business units and receiving positive feedback from PMs. Additionally, I oversee two simulators that generate test data for QA purposes, ensuring robust and scalable application performance: • A Flask-based Python simulator that generates data for legacy Airoes Controllers, APs, and clients. It runs as a dockerized application with integration of a device generator tool from another team. • A Java-based simulator that generates data for eWLC Netflow, syslogs, etc