Sr Administrator (Support & Operations)
About this role
Job Summary
Job Title: Data Integration Engineer – Level 2
Job Summary
We are seeking a highly skilled Data Integration Engineer (Level 2) to design, build, and manage enterprise-scale data integration solutions on Azure. This role requires strong expertise in cloud-native data services, integration patterns, DevOps practices, and L2 production support to ensure reliability, performance, and scalability of data platforms.
Key Responsibilities
- Design, develop, and maintain end-to-end data integration solutions across enterprise systems.
- Build scalable ETL/ELT pipelines using Azure Data Factory (ADF) and Azure Data Flows.
- Develop high-performance data processing solutions using Azure Databricks (ADB) and Python.
- Implement event-driven architectures using Azure Service Bus.
- Develop and manage serverless applications using Azure Functions.
- Design and expose APIs using Azure API Management (APIM).
- Build and maintain NoSQL data solutions using Cosmos DB.
- Manage secure access to secrets and credentials using Azure Key Vault.
- Monitor and troubleshoot applications using:
- Azure Application Insights
- Log Analytics Workspace
- Deploy and manage containerized applications using Azure Kubernetes Service (AKS).
- Implement CI/CD pipelines using Azure DevOps and GitOps practices via ArgoCD.
- Automate infrastructure provisioning and configuration using Terraform.
- Ensure effective use of Azure services for integration (eventing, messaging, API, compute).
- Provide Level 2 (L2) operational support, including:
- Incident management and resolution
- Root cause analysis (RCA)
- Performance optimization and system tuning
- Collaborate with architects, data engineers, and business stakeholders to deliver robust solutions.
- Implement best practices for security, monitoring, governance, and reliability.
Must-Have Skills & Experience
- Strong experience in Data Integration / Data Engineering.
- Hands-on expertise in:
- Azure Data Factory (ADF), Azure Databricks
- Confluent Kafka, Azure Event Hubs, Azure Service Bus Explorer
- Real-time data processing, Event-Driven Architecture, CDC, Micro-batch & Continuous Streaming
- Cosmos DB, Azure Blob Storage, Azure SQL, SQL
- PySpark, Python
- CI/CD Pipelines, Azure DevOps, Git, ETL Deployments
- Azure Monitor, Application Insights, Log Analytics, Alerts creation, Metrics analysis
- Azure Kubernetes Service (AKS)
- Control-M, Postman, Datadog
- Experience with:
- Azure Functions
- Azure Service Bus
- Azure API Management (APIM)
- Cosmos DB
- Monitoring and observability tools:
- Azure Application Insights
- Log Analytics Workspace
- Security:
- Azure Key Vault
- Containerization and orchestration:
- Azure Kubernetes Service (AKS)
- DevOps & deployment:
- Azure DevOps
- ArgoCD
- Infrastructure as Code:
- Terraform
- Strong understanding of Azure services related to integration (messaging, APIs, serverless, data pipelines).
- Experience in performance tuning and cost optimization on Azure.
- Exposure to API-led and microservices-based architectures.
- Proven operations/support (L2) experience in production environments.
- Good understanding of:
- Distributed systems
- Data modelling & data warehousing
- Cloud architecture and scalability patterns
Good-to-Have Skills
- Experience with legacy or enterprise ETL tools:
- IBM DataStage
- Advanced monitoring/observability tools:
- Datadog
- Splunk
- Knowledge of hybrid integration patterns.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, IT, or related field.
- Total integration experience of 12+ years with 6 to 8+ years of relevant experience in data integration, data engineering, or related roles.
- Azure certifications (preferred):
- Azure Data Engineer Associate
- Azure DevOps Engineer Expert
Key Responsibilities
Job Title: Data Integration Engineer – Level 2
Job Summary
We are seeking a highly skilled Data Integration Engineer (Level 2) to design, build, and manage enterprise-scale data integration solutions on Azure. This role requires strong expertise in cloud-native data services, integration patterns, DevOps practices, and L2 production support to ensure reliability, performance, and scalability of data platforms.
Key Responsibilities
- Design, develop, and maintain end-to-end data integration solutions across enterprise systems.
- Build scalable ETL/ELT pipelines using Azure Data Factory (ADF) and Azure Data Flows.
- Develop high-performance data processing solutions using Azure Databricks (ADB) and Python.
- Implement event-driven architectures using Azure Service Bus.
- Develop and manage serverless applications using Azure Functions.
- Design and expose APIs using Azure API Management (APIM).
- Build and maintain NoSQL data solutions using Cosmos DB.
- Manage secure access to secrets and credentials using Azure Key Vault.
- Monitor and troubleshoot applications using:
- Azure Application Insights
- Log Analytics Workspace
- Deploy and manage containerized applications using Azure Kubernetes Service (AKS).
- Implement CI/CD pipelines using Azure DevOps and GitOps practices via ArgoCD.
- Automate infrastructure provisioning and configuration using Terraform.
- Ensure effective use of Azure services for integration (eventing, messaging, API, compute).
- Provide Level 2 (L2) operational support, including:
- Incident management and resolution
- Root cause analysis (RCA)
- Performance optimization and system tuning
- Collaborate with architects, data engineers, and business stakeholders to deliver robust solutions.
- Implement best practices for security, monitoring, governance, and reliability.
Must-Have Skills & Experience
- Strong experience in Data Integration / Data Engineering.
- Hands-on expertise in:
- Azure Data Factory (ADF), Azure Databricks
- Confluent Kafka, Azure Event Hubs, Azure Service Bus Explorer
- Real-time data processing, Event-Driven Architecture, CDC, Micro-batch & Continuous Streaming
- Cosmos DB, Azure Blob Storage, Azure SQL, SQL
- PySpark, Python
- CI/CD Pipelines, Azure DevOps, Git, ETL Deployments
- Azure Monitor, Application Insights, Log Analytics, Alerts creation, Metrics analysis
- Azure Kubernetes Service (AKS)
- Control-M, Postman, Datadog
- Experience with:
- Azure Functions
- Azure Service Bus
- Azure API Management (APIM)
- Cosmos DB
- Monitoring and observability tools:
- Azure Application Insights
- Log Analytics Workspace
- Security:
- Azure Key Vault
- Containerization and orchestration:
- Azure Kubernetes Service (AKS)
- DevOps & deployment:
- Azure DevOps
- ArgoCD
- Infrastructure as Code:
- Terraform
- Strong understanding of Azure services related to integration (messaging, APIs, serverless, data pipelines).
- Experience in performance tuning and cost optimization on Azure.
- Exposure to API-led and microservices-based architectures.
- Proven operations/support (L2) experience in production environments.
- Good understanding of:
- Distributed systems
- Data modelling & data warehousing
- Cloud architecture and scalability patterns
Good-to-Have Skills
- Experience with legacy or enterprise ETL tools:
- IBM DataStage
- Advanced monitoring/observability tools:
- Datadog
- Splunk
- Knowledge of hybrid integration patterns.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, IT, or related field.
- Total integration experience of 12+ years with 6 to 8+ years of relevant experience in data integration, data engineering, or related roles.
- Azure certifications (preferred):
- Azure Data Engineer Associate
- Azure DevOps Engineer Expert
Skill Requirements
Job Title: Data Integration Engineer – Level 2
Job Summary
We are seeking a highly skilled Data Integration Engineer (Level 2) to design, build, and manage enterprise-scale data integration solutions on Azure. This role requires strong expertise in cloud-native data services, integration patterns, DevOps practices, and L2 production support to ensure reliability, performance, and scalability of data platforms.
Key Responsibilities
- Design, develop, and maintain end-to-end data integration solutions across enterprise systems.
- Build scalable ETL/ELT pipelines using Azure Data Factory (ADF) and Azure Data Flows.
- Develop high-performance data processing solutions using Azure Databricks (ADB) and Python.
- Implement event-driven architectures using Azure Service Bus.
- Develop and manage serverless applications using Azure Functions.
- Design and expose APIs using Azure API Management (APIM).
- Build and maintain NoSQL data solutions using Cosmos DB.
- Manage secure access to secrets and credentials using Azure Key Vault.
- Monitor and troubleshoot applications using:
- Azure Application Insights
- Log Analytics Workspace
- Deploy and manage containerized applications using Azure Kubernetes Service (AKS).
- Implement CI/CD pipelines using Azure DevOps and GitOps practices via ArgoCD.
- Automate infrastructure provisioning and configuration using Terraform.
- Ensure effective use of Azure services for integration (eventing, messaging, API, compute).
- Provide Level 2 (L2) operational support, including:
- Incident management and resolution
- Root cause analysis (RCA)
- Performance optimization and system tuning
- Collaborate with architects, data engineers, and business stakeholders to deliver robust solutions.
- Implement best practices for security, monitoring, governance, and reliability.
Must-Have Skills & Experience
- Strong experience in Data Integration / Data Engineering.
- Hands-on expertise in:
- Azure Data Factory (ADF), Azure Databricks
- Confluent Kafka, Azure Event Hubs, Azure Service Bus Explorer
- Real-time data processing, Event-Driven Architecture, CDC, Micro-batch & Continuous Streaming
- Cosmos DB, Azure Blob Storage, Azure SQL, SQL
- PySpark, Python
- CI/CD Pipelines, Azure DevOps, Git, ETL Deployments
- Azure Monitor, Application Insights, Log Analytics, Alerts creation, Metrics analysis
- Azure Kubernetes Service (AKS)
- Control-M, Postman, Datadog
- Experience with:
- Azure Functions
- Azure Service Bus
- Azure API Management (APIM)
- Cosmos DB
- Monitoring and observability tools:
- Azure Application Insights
- Log Analytics Workspace
- Security:
- Azure Key Vault
- Containerization and orchestration:
- Azure Kubernetes Service (AKS)
- DevOps & deployment:
- Azure DevOps
- ArgoCD
- Infrastructure as Code:
- Terraform
- Strong understanding of Azure services related to integration (messaging, APIs, serverless, data pipelines).
- Experience in performance tuning and cost optimization on Azure.
- Exposure to API-led and microservices-based architectures.
- Proven operations/support (L2) experience in production environments.
- Good understanding of:
- Distributed systems
- Data modelling & data warehousing
- Cloud architecture and scalability patterns
Good-to-Have Skills
- Experience with legacy or enterprise ETL tools:
- IBM DataStage
- Advanced monitoring/observability tools:
- Datadog
- Splunk
- Knowledge of hybrid integration patterns.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, IT, or related field.
- Total integration experience of 12+ years with 6 to 8+ years of relevant experience in data integration, data engineering, or related roles.
- Azure certifications (preferred):
- Azure Data Engineer Associate
- Azure DevOps Engineer Expert
Other Requirements
Job Title: Data Integration Engineer – Level 2
Job Summary
We are seeking a highly skilled Data Integration Engineer (Level 2) to design, build, and manage enterprise-scale data integration solutions on Azure. This role requires strong expertise in cloud-native data services, integration patterns, DevOps practices, and L2 production support to ensure reliability, performance, and scalability of data platforms.
Key Responsibilities
- Design, develop, and maintain end-to-end data integration solutions across enterprise systems.
- Build scalable ETL/ELT pipelines using Azure Data Factory (ADF) and Azure Data Flows.
- Develop high-performance data processing solutions using Azure Databricks (ADB) and Python.
- Implement event-driven architectures using Azure Service Bus.
- Develop and manage serverless applications using Azure Functions.
- Design and expose APIs using Azure API Management (APIM).
- Build and maintain NoSQL data solutions using Cosmos DB.
- Manage secure access to secrets and credentials using Azure Key Vault.
- Monitor and troubleshoot applications using:
- Azure Application Insights
- Log Analytics Workspace
- Deploy and manage containerized applications using Azure Kubernetes Service (AKS).
- Implement CI/CD pipelines using Azure DevOps and GitOps practices via ArgoCD.
- Automate infrastructure provisioning and configuration using Terraform.
- Ensure effective use of Azure services for integration (eventing, messaging, API, compute).
- Provide Level 2 (L2) operational support, including:
- Incident management and resolution
- Root cause analysis (RCA)
- Performance optimization and system tuning
- Collaborate with architects, data engineers, and business stakeholders to deliver robust solutions.
- Implement best practices for security, monitoring, governance, and reliability.
Must-Have Skills & Experience
- Strong experience in Data Integration / Data Engineering.
- Hands-on expertise in:
- Azure Data Factory (ADF), Azure Databricks
- Confluent Kafka, Azure Event Hubs, Azure Service Bus Explorer
- Real-time data processing, Event-Driven Architecture, CDC, Micro-batch & Continuous Streaming
- Cosmos DB, Azure Blob Storage, Azure SQL, SQL
- PySpark, Python
- CI/CD Pipelines, Azure DevOps, Git, ETL Deployments
- Azure Monitor, Application Insights, Log Analytics, Alerts creation, Metrics analysis
- Azure Kubernetes Service (AKS)
- Control-M, Postman, Datadog
- Experience with:
- Azure Functions
- Azure Service Bus
- Azure API Management (APIM)
- Cosmos DB
- Monitoring and observability tools:
- Azure Application Insights
- Log Analytics Workspace
- Security:
- Azure Key Vault
- Containerization and orchestration:
- Azure Kubernetes Service (AKS)
- DevOps & deployment:
- Azure DevOps
- ArgoCD
- Infrastructure as Code:
- Terraform
- Strong understanding of Azure services related to integration (messaging, APIs, serverless, data pipelines).
- Experience in performance tuning and cost optimization on Azure.
- Exposure to API-led and microservices-based architectures.
- Proven operations/support (L2) experience in production environments.
- Good understanding of:
- Distributed systems
- Data modelling & data warehousing
- Cloud architecture and scalability patterns
Good-to-Have Skills
- Experience with legacy or enterprise ETL tools:
- IBM DataStage
- Advanced monitoring/observability tools:
- Datadog
- Splunk
- Knowledge of hybrid integration patterns.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, IT, or related field.
- Total integration experience of 12+ years with 6 to 8+ years of relevant experience in data integration, data engineering, or related roles.
- Azure certifications (preferred):
- Azure Data Engineer Associate
- Azure DevOps Engineer Expert
Frequently Asked Questions
Is the salary disclosed for the Sr Administrator (Support & Operations) position at HCLTech?
The salary for this Sr Administrator (Support & Operations) role at HCLTech is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Sr Administrator (Support & Operations) position at HCLTech located?
This Sr Administrator (Support & Operations) role at HCLTech is based in Gautam Buddha Nagar, India. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
How do I apply for the Sr Administrator (Support & Operations) position at HCLTech?
Click the "Apply Now" button on this page. You will be redirected to HCLTech's official application portal hosted on successfactors where you can submit your application directly.
When was the Sr Administrator (Support & Operations) job at HCLTech posted?
This Sr Administrator (Support & Operations) position at HCLTech was posted on Sep 8, 2026. Apply as soon as possible — early applications are often reviewed first.
Sr Administrator (Support & Operations)
HCLTech
You'll be redirected to HCLTech's official application page on successfactors.