Headline

DevOps intern @sustainext | Ex-Intern @IEEE computer society | B.E information science @NMIT 26 | ML and Cloud Enthusiast

About

Hello everyone, I'm Pratheek Kachinthaya. I work across cloud infrastructure and data engineering, building data pipelines, deploying containerized applications, and automating infrastructure at scale. My toolkit spans Python, SQL, Azure, AWS, Docker, Kubernetes, Terraform, and CI/CD pipelines, with hands-on experience in ETL design, ensemble ML modelling, and cloud-native deployments on production workloads. I enjoy working at the boundary between infrastructure and data, where the question isn't just "does the pipeline run" but "does it scale, does it cost what it should, and does the output actually mean something to the business." That's the kind of problem I find worth solving. Outside structured work, I've built projects spanning real-time data processing pipelines, financial prediction systems on large structured datasets, and multi-source analytics platforms — all end-to-end, all shipped. Open to full-time opportunities in Data Engineering, Cloud/DevOps, Site Reliability Engineering, or Platform Engineering. Feel free to DM for conversations!

Location

Greater Bengaluru Area

AI stack

antigravity

claude code

codex

github copilot

hugging face

Weights & Biases Weave

Work experience

DevOps and Cloud Intern at Sustainext, Mar 2026 - Jul 2026 · 4 mo, Bengaluru, Containerized and shipped a production Django application end-to-end on AKS — authored a multi-stage Dockerfile, pushed versioned images to ACR, wrote Kubernetes manifests with RBAC role assignments for secure registry access, and configured VNet-integrated ingress — compressing environment setup from 3 days to under 4 hours. Built and rolled out a GitHub Actions CI/CD pipeline adopted by the team, benchmarking it against Jenkins across build speed, secrets management, and maintainability — reducing release cycle time by 65% and eliminating all manual deployment steps. Automated Azure infrastructure provisioning using Terraform and Ansible with reusable IaC modules and Bash deployment scripts, cutting per-environment setup time from 5 hours to under 20 minutes. Reduced projected AKS compute costs by 35% by modelling workload patterns and recommending HPA, VPA, and KEDA autoscaling configurations tuned to peak and off-peak traffic. Authored a technical evaluation of Azure–AWS cross-cloud integration via REST APIs, directly informing the client's multi-cloud architecture and IaC tooling decision.

Education

Bachelor's Degree, Information Science Engineering, nitte meenakshi institute of technology

Public links

github: https://github.com/Pratheek-05

pratheekkachinthaya.vercel.app: https://pratheekkachinthaya.vercel.app/