Chetana Nayak — Operations Associate

A Former Cloud Engineer specializing in Data engineering and DevOps. Passionate about driving an ML AI solution to be production-ready. 🧠 Skill set: Spark, Spark streaming, Kafka 🐍 Language: Python, Go, Shell ☁️ Cloud: vMware & GCP 💼 Databases: RDBMS, NoSQL, Postgres, Opensearch, S3 🎯 Orchestration tools: Airflow, MLflow, Argo 👨‍🔧 Devops CI/CD: Docker, Kubernetes, Gerrit, Jenkins 📊 BI/Visualization: Grafana, Tableau, PowerBI Data Engineering: - Live Spark Streaming pipelines processing 20k files from Kafka as a source and Opensearch, S3 as sinks. Data being used by various stakeholders for various ML use cases. - Building a Data warehouse with a Data lake that processes 20k files daily, on Mapr and metadata storage in Open search. - Development and production of an ELK-based anomaly detection solution to a leading telecom provider with 481TB of voice and call data generated per day and automated Dashboard design with complete visualization of 10 different use cases. - Data pipeline design for a Regression-based ML solution on the GCP cloud using Spark, Cassandra, and Python. - Development of production-ready NLP-based ticketing system with Argo, Seldon-core, Postgres, and Python running on Kubernetes cluster. - Hands-on experience with both SQL and NoSQL databases. MLOps and DevOps: - Build a production-ready Kubernetes cluster using Rancher on bare metal machines and attach physical volumes or NFS to make the cluster highly available. - Transform an existing solution to make it completely cloud-native. - Hands-on experience with popular orchestrators including Ansible, airflow, MLflow, Argo, Jenkins, git, etc.

Stackforce AI infers this person is a Data Engineering and Cloud Infrastructure expert with strong MLOps capabilities.

Location: Bengaluru, Karnataka, India

Experience: 9 yrs 10 mos