Role & responsibilities
Design and engineer a cloud-native, multi-tenant Apache data platform for on-prem and Azure.
Build platform services and operators using Python for lifecycle automation.
Standardize Kubernetes deployment patterns for Apache stack components (Helm, manifests, policies).
Build and maintain hardened Docker images for all platform runtimes and services.
Architect and operate Spark platform capabilities for batch and streaming workloads.
Implement and maintain Iceberg-based Lakehouse platform foundations and table governance controls.
Build CI/CD platform pipelines in Azure DevOps for automated build, test, release, and rollback.
Implement platform security controls using TLS/SSL, OAuth, RBAC, secrets management, and Vault.
Engineer observability using Prometheus, Grafana, logging pipelines, SLI/SLO dashboards, and alerting.
Lead platform incident response, root-cause analysis, patching, upgrades, and capacity engineering.
Partner with security, compliance,



and consuming teams to onboard workloads and enforce enterprise standards along with CVE remediation

Preferred candidate profile
Solid full-stack engineer with deep expertise in Python REST APIs, Kubernetes.
Advanced Python scripting and automation for platform provisioning, validation, and operational runbooks.
Deep Kubernetes expertise (scheduling, networking, storage, security, scaling, troubleshooting).
Hands-on Docker expertise for image lifecycle, hardening, and runtime optimization.
Expert Apache Spark platform knowledge (cluster tuning, job isolation, batch + streaming)
Robust Apache Iceberg platform understanding (catalogues, partitioning, compaction, governance).
CI/CD engineering using Azure DevOps, including policy-driven release controls.
Solid observability and reliability engineering using Prometheus and Grafana.

📌 Python Kubernetes Developer Chennai/ Bangalore (India)
🏢 Tech Mahindra
📍 India