Nikhil Chennu

Responsible for developing various batch and event based ETL pipelines using spark, python, AWS Batch and AWS EMR, processing enrichments for millions of records per day. Built machine learning model inference pipelines exposed over rest API using async based framework Fast API. Optimised run times of various micro-services using concurrent / parallel processing and part of migration of micro-services to Kubernetes which provides better availability, visibility, monitoring using logentries and datadog

Part of NGINX Controller analytics module development team, enabling better monitoring & management of metrics/events data and providing API driven development support.Worked on containerized and microservices based architecture, enabling different REST based API's and gRPC based communication between services, using golang . Managed authentication using JWT tokens , metrics/events processing using NATS / Kafka message brokers

Engineered and Developed cloud automation solutions using python programming , AWS cloud and machine learning techniques like clustering, regression, neural networks and dimensionality reduction Worked on Various AWS services like EC2, Lambda, AWS Batch, IAM, CloudWatch, API Gateway, S3, Elastic Search, Elastic Cache (Redis) and Dynamo DB.

This Research Internship experience introduced various concepts of data mining and worked on a research problem "Image Compression using Pattern Mining" https://www.researchgate.net/publication/328372307_Lossy_Image_Compression_using_Freq