T
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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