Big Data Platform Engineer
At a glance
Mid-level Data Engineering role at Two95 International Inc. Remote, India · full-time.
Pay not stated Data Platform Engineer salary
remoteroles summary, based on the employer's posting.
What you'll do
- Run and support the AKS infrastructure behind the Big Data platform, including upgrades, patching and capacity planning
- Administer Apache NiFi, Azure Event Hub and Azure Functions, covering operations, configuration and troubleshooting
- Build and maintain Azure DevOps CI/CD pipelines and automate infrastructure provisioning with Terraform and Bicep
- Track platform health through Azure Monitor and Log Analytics, then investigate infrastructure, networking and platform faults
- Work with Data Engineering teams on platform enablement and strengthen security, governance and production reliability
What you bring
- At least eight years in IT, including five or more in cloud infrastructure engineering
- Four or more years with Kubernetes and three or more supporting enterprise data platforms
- Hands-on experience with Apache NiFi and Azure Event Hub, both essential, plus Azure Functions
- At least two years with Azure Data Services and three or more in DevOps or SRE practices
- Strong AKS administration skills and practical Terraform, Bicep and ARM Templates experience
Who this fits
This mid-level role suits an engineer with deep Azure, Kubernetes and data-platform operations experience. It is a full-time remote position based in India.
From the employer
Experience Requirements
● 8+ years of overall IT experience ● 5+ years of experience in Cloud Infrastructure Engineering ● 4+ years of experience working with Kubernetes platforms ● 3+ years of experience supporting enterprise-scale Data Platforms ● 3+ years of experience in DevOps/SRE practices ● 2+ years of experience working with Azure Data Services
Mandatory Skills
Candidates must possess strong hands-on experience in the following areas: ● Apache NiFi ● Azure Event Hub ● Azure Functions ● Enterprise-scale Data Platform Administration These are core and non-negotiable requirements. Profiles without hands-on experience in Apache NiFi and Azure Event Hub will not be considered.
Requirements
1. Azure Kubernetes Service – AKS
Strong Expertise
● AKS cluster deployment and administration ● Cluster upgrades and patch management ● Node pool management ● Ingress Controllers, including NGINX and Application Gateway ● RBAC implementation ● AKS security hardening ● Autoscaling using HPA, VPA, and Cluster Autoscaler ● Persistent storage management ● Troubleshooting cluster issues ● Network policies
Experience
● Production support of AKS environments ● Multi-node and multi-environment AKS setups ● High availability and disaster recovery implementation
2. Kubernetes and Azure Networking
Kubernetes Networking ● Kubernetes networking concepts ● Services, Ingress, and Load Balancers ● DNS resolution ● Pod-to-Pod communication ● Pod-to-Service communication ● Network Policies ● Service Mesh concepts, preferably Istio ● CNI Architecture
Azure Networking
● Virtual Networks ● Subnets ● Private Endpoints ● Peering ● Network Security Groups ● User Defined Routes ● Azure Firewall ● VPN connectivity
3. Docker and Containerization
● Docker image creation and optimization ● Container lifecycle management ● Registry management ● Security scanning ● Multi-stage builds ● Container troubleshooting ● Azure Container Registry ● Image versioning and governance
4. Azure DevOps and CI/CD
CI/CD Expertise ● Azure DevOps Pipelines ● YAML pipelines ● Build and Release pipelines ● Git repositories ● Branching strategies
Infrastructure Deployment
● Infrastructure as Code ● ARM Templates ● Bicep ● Terraform
Automation
● Deployment automation ● Environment promotion ● Release management
5. Monitoring and Observability
Azure Monitor
● Monitoring strategy implementation ● Alert configuration ● Dashboard creation
Log Analytics
● KQL query development ● Performance analysis ● Troubleshooting
Application Monitoring
● Azure Application Insights ● Distributed tracing ● Metrics collection
AKS Monitoring
● Cluster health monitoring ● Pod performance monitoring ● Resource optimization
6. Azure Event Hub Candidates must have strong hands-on experience in: ● Event Hub architecture ● Namespace management ● Consumer groups ● Scaling and throughput units ● Monitoring and troubleshooting ● Security and access control 7. Azure Functions Candidates must have hands-on experience in: ● Deployment and operations support ● Function App management ● Scaling configuration ● Managed Identity integration ● Monitoring and troubleshooting ● CI/CD deployment 8. Apache NiFi Candidates must have strong hands-on experience in: ● NiFi cluster setup and maintenance ● Flow deployment ● Security configuration ● Performance tuning ● Monitoring ● Troubleshooting Preferred ● NiFi Registry ● Cluster scaling ● High availability implementation 9. Infrastructure as Code Must-Have Skills ● Terraform ● Bicep ● ARM Templates
Required Capabilities
● Platform provisioning ● Environment consistency ● Version-controlled infrastructure Good-to-Have Skills Platform Engineering ● GitOps using ArgoCD or Flux ● Platform automation ● Self-service platform concepts ● Internal Developer Platform Observability ● Grafana ● Prometheus ● OpenTelemetry Security ● Microsoft Defender for Cloud
● Kubernetes security best practices ● Container security ● Secrets management ● Vulnerability management Data Platform ● Azure Data Factory ● Synapse Analytics Cloud ● Multi-region architecture ● Disaster recovery planning ● Landing Zone implementation Scripting ● PowerShell ● Bash ● Python
Key Responsibilities
● Manage and support AKS-based Big Data platform infrastructure. ● Administer Apache NiFi, Azure Event Hub, and Azure Functions. ● Implement and maintain CI/CD pipelines using Azure DevOps. ● Monitor platform health using Azure Monitor and Log Analytics. ● Troubleshoot platform, networking, and infrastructure issues. ● Implement infrastructure automation through Terraform and Bicep. ● Ensure platform security, governance, and compliance. ● Collaborate with Data Engineering teams for platform enablement. ● Perform upgrades, patching, capacity planning, and optimization. ● Support production incidents and platform reliability initiatives.