Azure Data Engineer

Job Description:

Responsibilities

• Design and architect scalable data platforms and pipelines using Azure services such as Azure Data Factory, Azure Databricks, and ADLS.
• Build and optimize complex ETL/ELT pipelines for batch and real-time data processing using Databricks/Spark.
• Develop data models, data warehouse solutions, and optimized storage structures using Azure services.
• Implement data quality checks, validation frameworks, and monitoring to ensure reliable and accurate data.
• Optimize data pipelines and infrastructure for performance, scalability, and cost efficiency.
• Collaborate with business, analytics, and product teams to deliver data solutions aligned with business needs.

Qualification & Expeirence

• 5–7 years of hands-on experience in data engineering with strong expertise across the Microsoft Azure ecosystem.
• Proven experience working with Azure Data Factory, Azure Databricks, ADLS, and Apache Spark for building scalable and efficient data pipelines.
• Strong programming skills in Python and advanced SQL, with the ability to write optimized, reusable, and production-grade code.
• Solid understanding of data warehousing concepts, data modeling techniques, and modern big data architectures.
• Hands-on experience with DevOps/DataOps practices, including CI/CD pipelines, Git-based version control, and deployment of data solutions in production environments.
• Good understanding of data quality frameworks, validation techniques, monitoring, and troubleshooting to ensure reliable and accurate data systems.