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Senior Technical Specialist

BengaluruOn-siteDirector

Good timing - competition is buildingPosted 4d ago

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The job post

1448 words · from HCLTech's careers site

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

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