About the Role

The ideal candidate should have 6+ years of hands-on experience in data engineering, with a strong background in building end-to-end data solutions, working with modern data architectures, and leveraging Azure cloud services to deliver scalable and secure data platforms.
 

Key Responsibilities

Design, develop and manage data pipelines on Microsoft Azure for internal and external data sources. Develop ingestion frameworks for batch and real-time data. Ensure data pipelines are optimized for reliability and scalability. Ensure the scalability, security, and performance of our cloud architecture while aligning with business goals. Work closely with solution architect, backend developers, data governance specialists
 

Technical Responsibilities

Collaborate with business stakeholders to translate functional requirements into scalable technical solutions. Hands-on experience with Microsoft Fabric platform in building end-to-end data solutions. Hands-on experience with building pipelines using MS Fabric. Build and optimize data lake zones (raw, curated, consumption) Proficiency in developing business and dataflow logic for data processing using tools like PySpark, TSQL, Stored Procedures Experience implementing message queues using Azure Service Bus Integrate cloud-based solutions with on-premises systems. Implement infrastructure as code (IaC) solutions using Terraform for consistent, automated provisioning In-depth knowledge of Azure architecture components, including compute, storage, networking, and security. Optimize cloud storage solutions for performance and cost. Establish monitoring and logging solutions using Azure Monitor, Log Analytics, Application Insights, and third-party tools. Configure automated scaling solutions to handle workload fluctuations. Create and maintain comprehensive architecture documentation, including diagrams, processes, and technical specifications