Design, develop, and implement data engineering solutions on Microsoft Azure for enterprise-scale applications.
Build and maintain scalable data pipelines and frameworks using Databricks, PySpark, and Azure services.
Collaborate with cross-functional teams to ensure high-quality data delivery and support analytics, machine learning, and AI initiatives.
Develop and maintain data pipelines using Databricks PySpark (structured streaming and batch processing).
Work with Python for data processing, automation, and integration tasks.
Design and implement solutions on Azure services including ADLS, EventHub, Event Grid, SQL Data Warehouse, Azure Functions, and serverless architectures.
Collaborate on Terraform implementations for infrastructure as code (theory knowledge required, practical experience preferred).
Ensure proper handling of SQL and NoSQL databases for large-scale data processing.
Support data engineering operations in cloud environments with high data volumes.
Collaborate with global teams to integrate data solutions into business processes.
Maintain best practices for data security, governance, and quality.
requirements-expected :
6–8 years of experience in data engineering, preferably with Microsoft Azure.
Strong expertise in:
Python
SQL and NoSQL databases
Databricks PySpark (structured streaming and batch)
