Kubernetes Data Platform

• TCS HIRING

: Kubernetes Data Platform

BANGALORE

6-10 YEARS

IMMEDIATE JOINERS ONLY UPTO 30 DAYS

• Design, build, and maintain production-grade Kubernetes platforms.
• Deploy and operate Stackable Data Platform services on Kubernetes.
• Engineer scalable and resilient multi-tenant platform architectures.
• Develop self-service platform capabilities for data engineering and AI teams.
• Drive platform standardisation and engineering best practices.

Data Platform Services

• Deploy, configure, and optimise Apache Spark services and workloads.
• Design and support Apache Kafka clusters for streaming workloads.
• Integrate data services with S3-compatible Object Storage platforms.
• Support data lake, analytics, and AI/ML platform use cases.
• Enable workload migration from legacy Hadoop platforms to Kubernetes-native services.

Automation & DevOps

• Implement GitOps-based deployment pipelines using ArgoCD.
• Automate platform provisioning, upgrades, validation, and operational activities.
• Improve CI/CD pipelines and platform release processes.

Reliability & Operations

• Lead troubleshooting of production platform issues.
• Conduct Root Cause Analysis (RCA) and implement preventative improvements.
• Implement monitoring, observability, alerting, and capacity management practices.
• Drive platform resiliency, availability, backup, and disaster recovery strategies.
• Support platform upgrades, patching, and lifecycle management.

Security & Governance

• Implement Kubernetes security best practices.
• Manage RBAC, secrets, certificates, and network policies.
• Support data governance, platform compliance, and operational controls.
• Ensure secure multi-tenant operation across platform services.

Skills & Experience

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

• Strong 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