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 environments.
- 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 (Bengaluru)
🏢 Tata Consultancy Services
📍 Bengaluru