About the Role We are looking for an experienced Azure Cloud Engineer to join our Managed Services / Cloud Reliability team. The ideal candidate should have strong hands-on experience in Azure infrastructure, AKS, networking, identity, monitoring , and CI/CD automation . You will be responsible for ensuring high availability, performance, security , and operational stability of cloud environments in production. Key Responsibilities Manage, operate, and maintain Azure cloud infrastructure across multiple environments (Dev / QA / Prod). Deploy, configure, and troubleshoot services on Azure (VMs, App Services, Storage, Key Vault, Azure SQL, Networking) . Administer and maintain Azure Kubernetes Service (AKS) and containerized workloads (Docker). Implement and maintain Infrastructure as Code using Terraform / ARM / Bicep . Manage CI/CD pipelines using Azure DevOps (Build & Release automation). Monitor and analyze resource utilization, performance, and incidents using Azure Monitor / Log Analytics . Ensure adherence to security, compliance, and access controls using Azure AD & RBAC . Troubleshoot production issues and participate in on-call / incident response as required. Optimize cloud cost, storage tiers, and compute scaling strategies. Must-Have Skills Strong hands-on experience in Azure Cloud Services AKS / Kubernetes administration & Docker VNet, Subnets, NSG, Load Balancer, VPN Gateways, Firewalls (Networking essentials) Terraform / ARM Templates / Bicep (Infrastructure as Code) Azure DevOps Pipelines (CI/CD) Azure Monitor, Log Analytics, Alerts & Diagnostics Azure AD / IAM / RBAC / Key Vault (Identity & Security) Good troubleshooting & incident management skills
Job Description: Data Engineer (Azure Databricks) About the Role We are looking for a passionate Data Engineer experienced in building scalable, high-performance data platforms on Azure Databricks . The ideal candidate will have strong hands-on experience in ETL/ELT pipeline development , data modeling , and performance optimization , with a focus on delivering clean, reliable, and business-ready data. Key Responsibilities Design, develop, and optimize end-to-end ETL/ELT pipelines using Azure Databricks, Synapse, and Data Factory (ADF) Implement Medallion / Delta Lake architectures ensuring quality and consistency of data Build and maintain data lake and warehouse solutions supporting analytical and reporting needs Optimize Spark jobs and pipeline performance through tuning and best practices Develop data models (Star/Snowflake) and implement SCD Type 1 & 2 for dimensional data Automate data ingestion, transformation, and validation to improve efficiency and reduce manual work Integrate data from multiple sources (APIs, databases, structured/unstructured files) Collaborate with cross-functional teams across data, BI, and business units to ensure data readiness Manage and deploy code using Azure DevOps and version control systems Maintain documentation and follow SDLC best practices in agile environments Required Skills 35 years of experience in Data Engineering Proficient in Python, PySpark, SparkSQL, and Advanced SQL Strong hands-on experience in Azure Databricks, ADF, ADLS, Synapse Excellent understanding of data modeling and warehouse design Experience in performance tuning and pipeline optimization Working knowledge of CI/CD, Git, and Azure DevOps Good understanding of data governance, metadata, and automation frameworks Good to Have Exposure to AWS or multi-cloud environments Knowledge of Power BI / data visualization integration Experience working with API-based data ingestion Certifications such as Databricks Data Engineer Associate or Azure Data Engineer Associate Certifications Databricks Data Engineer Associate Microsoft Certified: Azure Data Engineer Associate Azure Data Fundamentals