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