Azure Data Engineer

DATAECONOMY Inc; Hyderabad; On-site; INR 1,200,000 - 1,900,000; Full time

Job summary

DATAECONOMY Inc invites an Azure Data Engineer to design, develop, and maintain scalable cloud-based data solutions on the Microsoft Azure platform. You will build and optimize data pipelines, data lakes, and data warehouses to support analytics and business intelligence initiatives.

Responsibilities include integrating data from APIs, databases, flat files, and streaming platforms, ensuring data quality and security, and implementing CI/CD for data platforms, while collaborating with analysts

Responsibilities

• Design and implement scalable data pipelines using Azure services.
• Develop and maintain ETL/ELT workflows for structured and unstructured data.
• Build and optimize data solutions using Azure cloud technologies.
• Integrate data from multiple sources including APIs, databases, flat files, and streaming platforms.
• Create and manage data lakes, data warehouses, and medallion architectures.
• Ensure data quality, governance, security, and compliance standards.
• Monitor and troubleshoot production data workflows and performance issues.
• Collaborate with data analysts, DevOps, and business stakeholders.
• Implement CI/CD pipelines and infrastructure automation for data platforms.
• Optimize SQL queries and improve overall data processing performance.

Job description

We are seeking a skilled Azure Data Engineer to design, develop, and maintain scalable cloud-based data solutions on the Microsoft Azure platform. The ideal candidate will have expertise in data integration, ETL/ELT pipelines, big data technologies, and cloud data warehousing to support analytics and business intelligence initiatives.

Key Responsibilities

• Design and implement scalable data pipelines using Azure services.
• Develop and maintain ETL/ELT workflows for structured and unstructured data.
• Build and optimize data solutions using Azure cloud technologies.
• Integrate data from multiple sources including APIs, databases, flat files, and streaming platforms.
• Create and manage data lakes, data warehouses, and medallion architectures.
• Ensure data quality, governance, security, and compliance standards.
• Monitor and troubleshoot production data workflows and performance issues.
• Collaborate with data analysts, DevOps, and business stakeholders.
• Implement CI/CD pipelines and infrastructure automation for data platforms.
• Optimize SQL queries and improve overall data processing performance.