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Python Kubernetes Developer - Chennai/ Bangalore

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Hybrid

Python Kubernetes Developer - Chennai/ Bangalore

Tech Mahindra

Python Kubernetes Developer - Chennai/ Bangalore

Skills

DockerPythonGrafanaPrometheusKubernetesComplianceAzure

5 days ago

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Important information


Contract type:

Permanent

Salary:

₹1,800,000 – ₹3,300,000 / year

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

14 October 2026

What they need


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

  • Strong 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)
  • Strong Apache Iceberg platform understanding (catalogues, partitioning, compaction, governance).
  • CI/CD engineering using Azure DevOps, including policy-driven release controls.
  • Strong observability and reliability engineering using Prometheus and Grafana.

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