Role & responsibilities

Mandatory Skills

Kubernetes
5+ years of hands-on Kubernetes platform engineering experience.
Cluster design, deployment, administration, and troubleshooting.
Platform upgrades, scaling, and lifecycle management.
Kubernetes security and multi-tenancy.
High Availability (HA) and disaster recovery design.

Data Platform Technologies
Robust experience with Stackable Data Platform or comparable Kubernetes-native data platforms.
Apache Spark (PySpark and/or Scala).
Spark SQL and performance tuning.
Apache Kafka administration and operations.
Real-time and batch data processing architectures.

Storage
S3-compatible Object Storage (MinIO, Ceph, FlashBlade).
Object storage performance optimisation.
Data lifecycle management, backup, and recovery.

DevOps & Automation
Helm.
ArgoCD.
Terraform.
GitOps.
CI/CD implementation and automation.

Preferred Skills
Trino.
NIFI
Airflow.
Prometheus.
Grafana.
Vault.
Keycloak.

Nice to Have




Telecom or Network Domain experience.
AI/ML platform engineering.
Kubeflow.
OpenMetadata.
DataHub.

Experience Required
6+ years of overall platform engineering experience.
5+ years operating Kubernetes in production settings.
Experience supporting mission-critical enterprise data platforms.
Experience delivering production services in hybrid cloud environments.

What Success Looks Like

The successful candidate will demonstrate the ability to:

Independently build and operate Kubernetes clusters

Deploy and manage Stackable platform services

Scale Spark and Kafka workloads for enterprise use cases

Design resilient object storage integrations

Automate platform operations using GitOps and Infrastructure as Code

Troubleshoot complex platform incidents and perform effective RCA

Drive platform reliability, security, and operational excellence

📌 Kubernetes Data Platform Hyderabad (India)
🏢 Tata Consultancy Services
📍 India