Azure Data Engineer

• Design, develop, and maintain scalable data pipelines and data processing frameworks on the Azure cloud platform
• Build and optimize batch and real-time data processing solutions using Databricks and PySpark (Structured Streaming & Batch)
• Develop robust data ingestion pipelines using Azure Event Hub, Event Grid, and Azure Data Lake Storage (ADLS)
• Implement serverless and event-driven architectures using Azure Functions and other Azure-native services
• Design and manage data storage solutions using SQL and NoSQL databases
• Support data transformation and analytics workflows using Azure SQL Data Warehouse / Synapse
• Implement infrastructure automation and provisioning using Terraform
• Collaborate with cross-functional teams to design efficient and secure data solutions aligned with business requirements
• Ensure data platform reliability, performance optimization, and scalability

• 8-10 years of experience in data engineering and cloud-based data platform development
• Strong hands-on expertise in Microsoft Azure data ecosystem
• Advanced programming skills in Python
• Experience working with SQL and NoSQL databases
• Strong expertise in Databricks and PySpark (Structured Streaming and Batch Processing)
• Hands-on experience with Azure Data Lake Storage (ADLS), Event Hub, Event Grid, Azure Functions, and SQL Data Warehouse
• Experience designing serverless and event-driven data architectures
• Knowledge of Terraform for infrastructure as code (theoretical understanding required; practical experience preferred)
• Experience with Azure Data Factory and ARM Templates
• Knowledge of Kubernetes and Google Cloud Platform
• Exposure to Machine Learning and Artificial Intelligence workflows

You Should Possess the Ability to:

• Architect and implement scalable cloud-native data engineering solutions
• Develop efficient real-time and batch data processing pipelines
• Optimize data storage, transformation, and retrieval processes for performance and reliability
• Implement infrastructure automation and maintain reproducible environments
• Collaborate effectively with data scientists, analysts, and platform teams
• Troubleshoot and resolve complex data pipeline and integration issues
• Ensure data governance, security, and compliance within cloud environments

• Opportunity to work on modern cloud-based data engineering platforms built on Microsoft Azure
• Exposure to large-scale data processing, real-time streaming, and serverless architectures
• A collaborative engineering environment focused on innovation and scalable data solutions
• Opportunities to work with advanced analytics, machine learning, and AI-driven use cases
• Continuous learning and growth in cloud, big data, and modern data engineering practices